Mental imagery is important in the development and maintenance of psychological disorders and well‐being but has been neglected in people with intellectual disabilities. A detailed idiographic analysis of the lived experience of mental imagery in this population is presented.This qualitative study uses interpretative phenomenological analysis (IPA). It involved inclusive research methods with people with intellectual disabilities and other stakeholders .Ten individual semi‐structured interviews were conducted with people with mild–moderate intellectual disabilities. Participants were opportunistically sampled through organisations providing community services to people with intellectual disabilities in the UK. Two men and eight women (mean age 43 years) participated. Interviews were audio‐recorded and analysed using IPA.People with intellectual disabilities are able to experience a range of rich and detailed mental images across all sensory modalities. Participants reported changes in affect based on mental imagery, and an ability to experience both spontaneous and deliberate mental images. The emotional saliency of the object of mental imagery appeared to influence participants' ability to engage with imagery. A number of adaptations make mental imagery more accessible and easier to report. The ability of people with intellectual disabilities to experience vivid mental imagery has important clinical implications for the use of a range of mental imagery interventions with this population.The need to consider mental imagery interventions for this population, and how these can be adapted to ensure accessibility is a priority for people with intellectual disabilities and psychological disorders. People with intellectual disabilities can experience and engage with rich and vivid mental imagery across different sensory modalities.Specific techniques and strategies that facilitate or impede the use of mental imagery in people with intellectual disabilities are described.There are implications for using psychological interventions that incorporate mental imagery  with people with intellectual disabilities.Mental imagery refers to the internal mental processes whereby perceptual information is accessed from memory  and is described as ‘seeing with the mind's eye’ although it can be experienced across sensory modalities  and non‐verbal methods (creating an image) to explore the lived experience of mental imagery in people with intellectual disabilities.This qualitative study was designed and conducted from a phenomenological perspective. The project was developed via an inclusive research approach. This involved using co‐production with two separate groups, a group of people with intellectual disabilities (named the STAR Group), and a Stakeholder Group . Both groups were involved in the project conception, design and analysis. Whilst neither group were directly involved in writing this paper, due to the iterative nature of their input throughout the research process, their voice forms part of the authorial voice.The semi‐structured interview schedule was co‐designed with the STAR and Stakeholder Groups. A range of topics were gathered  and presented in accessible formats to the groups. Once topics for exploration in the interviews were agreed through group consensus, both groups were again consulted to discuss and agree experiential exercises to be included in the interview, and the format of the image participants would create. Adaptations to improve accessibility to the interview schedule were adopted.Participants took part in one‐to‐one interviews. A favourable ethical opinion was given by a United Kingdom University Research Ethics Committee (Ref: 124/20–21). Informed consent was obtained from all participants.Participants were recruited through opportunistic sampling from community settings specifically serving people with intellectual disabilities  participated.The first author conducted individual interviews with 10 people with mild‐to‐moderate intellectual disabilities on one occasion. Eight women and two men aged 25–54 , glues and a selection of magazines. Notes were taken on how participants approached the activity . Interviews were audio‐recorded and transcribed verbatim with pseudonymisation to ensure confidentiality.Interviews lasted between 48 and 93 min . The STAR Group met four times over 5 months . Analysis was conducted during these meetings and during meetings with academic researchers, in an iterative process.The STAR and Stakeholder Groups conducted all stages of analysis including recording initial impressions, identifying initial themes, making changes to the structure of superordinate and subordinate themes and choosing quotes to illustrate subthemes. The groups compared themes to find patterns across participants and develop the final set of themes. This was facilitated through using sticky notes to concretely represent themes from different participants which could be physically moved by group members. Discussions within the research team highlighted areas where the link between interpretative comments or themes and the raw data was less clear and allowed for consideration of how the researchers' own beliefs and preconceptions might influence analysis.Quality assurance  whilst simultaneously finding other sensory aspects (the sticky feeling) unpleasant, and noting the coldness of the ice cream demonstrates the complexity and idiosyncratic nature of mental imagery:OHThis chocolate ice cream…ZadieIt's in a cone, with a chocolate flake and you lick it, and it goes down in the cone really fast.OHAnd is it a bit melting this chocolate ice cream?ZadieYeah. And I've got it all round my face and hands.OHHow does it feel on your hands?ZadieSticky and horrible.OHWhat does it taste like?ZadieOh, lovely!OHAnd is it very cold the ice cream?ZadieVery cold.Zadie had not experienced mental imagery before the interview but quickly understood what was meant by the term and subsequently tactile experience of her image, including the weight, texture and temperature of an imagined orange:OHWhat does it feel like?BethanyCold.OHIt feels cold, yeah.BethanyYou can peel it off and start eating it.OHYeah. Is it heavy or is it light, this orange?BethanyHeavy.OHIt feels quite heavy. And what does the skin feel like, it feels cold, but is it smooth or bumpy?BethanySmooth.Participants could experience rich and detailed imagery when reporting several aspects of a single sensory modality. Bethany was able, with prompting, to report several aspects of the smell, as Bethany later described ‘[it] smells of orange… it is a nice smell’. The ability to experience an image across several sensory modalities simultaneously was notable, as was experiencing different aspects of one sensory modality, both of which provided a vividness to the image.These quotes illustrate the ability of participants to experience vivid imagery across all sensory modalities, including surprising, extraordinary and humorous. Whilst in theme one participants' mental imagery could be predictably transformed, remaining under their control, this theme included unbidden, unexpected aspects of imagery. Examples of this included Maria discovering her imagined orange was rotten ‘No, it's gone off, sorry… it's bad for you, it will give you an upset tummy’ and Peter spontaneously visualising ‘A big ball in my bedroom [laughs]… It's like all different colours… It's bouncing, bouncing, bouncing, bouncing all in my room’. The inclusion of movement in an image (often unexpected) gave a sense of the unpredictability of imagery, with it shifting and developing in different directions, seemingly only partially controlled by the participant.This theme encompassed a range of experiences whereby images could be mental imagery abided closely by real life rules . One participant with dyspraxia could not imagine catching an orange due to their physical limitations. Karla's mental imagery abided by the real‐life rule of wearing a face mask, preventing her from eating an orange: ‘I can't feel… I can't eat it with my mask’.A dichotomy of experiences emerged, whereby for some participants their mental imagery could be used to do impossible things such as journeying into space. Maria was especially interested in unicorns, as reflected in her created image and her interview. With little prompting, and a sense of this image unfolding in her mind's eye, she fluently described a magical nightscape:OHImagine the sun going down in the evening…MariaIt's shining and it's yellow and bright and the moon is out and all the stars are out and all the lovely stars are twinkling in the sky and the moon is full, a full moon and a happy moon, not a sad moon. And he's got his eyes shut, it's bedtime and the stars are out twinkling down and the sun is…and the sun is awake because it's night time and it's yellow due to the sunshine, and then that's it. And the stars have unicorns around it; all round the stars are unicorns.However, for several participants, impossible scenarios and was not restrained by the everyday. They had a confidence and fluency around experiencing and reporting such imagery.For such participants mental imagery could be used to explore be shared with others:OHWhat noise are the waves making on the beach?ClarissaShshshsh. Beautiful!OHAnd it's quite breezy. And can you hear any seagulls?ClarissaYeah… [makes squawking noise]OHAnd are the dogs playing in the water?ClarissaYeah, they're barking away.Several participants used noise and gestures to convey their mental imagery to the interviewer, acknowledging that whilst mental imagery is an intrinsically internal experience, it can also shared, relational space to be created between the interviewer and participant. Whilst imagery was generated within the participants internal world, the process of communicating with the other and being prompted by the ideas and suggestions of the interviewer, led to a collaborative and iterative process of further sharing and elaboration of imagery.This elicitation of imagery required a This theme encompasses the wide range of mental images experienced by participants. Whilst engaging with mental imagery was both personal and idiosyncratic, it could be shared with others and include playful, unexpected aspects.strong and powerful and encompassed a wide range of different emotions, such as surprise, delight, disgust and fear. They were communicated both verbally and nonverbally , which conveyed the intensity of these emotional responses. When experiencing mental imagery, participants could describe their associated emotions, and respond to emotional reactions ‘as if’ they occurred in real life .Almost all participants described changes in affect linked to experiencing mental imagery. Changes in feelings could be a range of emotional and behavioural responses to mental imagery including exploring pleasurable images in different sensory modalities:OHSo let's imagine…on your bedside table there's a really big, lovely bunch of flowers.ZadieOh, that would be lovely! Red, yellow, pinks, oranges, all different colours.OHWhat do they smell like?ZadieReally, really nice, with a nice vase.Zadie demonstrated ZadieThere's gonna be a big thunderstorm… All the clouds come, they're getting closer and closer…and I'm a bit scared so I go to my room and hide under the duvet.Conversely, other images prompted anxiety, and associated behaviour change:both easier or harder to imagine things that were important or held emotional significance.Participants' ability to engage with mental imagery around emotionally salient items varied in unpredictable ways. Participants found it strength of affect generated was noticeable. Clarissa spoke about her neighbour's cat Marley throughout her interview. She was very fond of the cat and generated, developed and transformed mental images of it. Subsequently, however, imagining Marley impeded her mental imagery. Marley was not allowed in Clarissa's house, and when asked to imagine Marley in her bedroom she had a strong emotional response:ClarissaErgh! That's horrible. I wouldn't allow it.OHYou don't like it do you? I can see from your face.ClarissaShe wouldn't be allowed upstairs. She wouldn't be allowed up there.For some, focusing on a familiar and loved object, such as a pet, facilitated their ability to generate mental imagery. However, asking people to engage with mental imagery around other precious items could impede imagery as people protected these items from perceived harm or disrespect. For several participants, the OHGet on the bed and start jumping up and down! Can you imagine?ClarissaNo!OHJust imagine that in your head.ClarissaIt'll break it….OHCan you imagine doing it?ClarissaNope.OHCan you imagine me doing it?ClarissaNo!Another example of the impact of the emotional saliency of objects of the participant's ability to incorporate them into mental imagery occurred when Clarissa was asked to imagine herself jumping on her bed:It transpired the bed was a gift from Clarissa's parents and she was reluctant to treat this precious item disrespectfully.Understanding the idiosyncratic links between the emotional saliency of an object and the impact this may have on a persons' ability to engage with mental imagery around it can be subtle, requiring careful exploration.was a pre‐existing skill they could effortlessly engage in. For example, Peter frequently spontaneously reported complex mental imagery across sensory modalities in a fluent and eloquent manner, reflecting the ease with which he experienced and could report these phenomena. For others it was an untapped resource, they were initially unaware of but could quickly and easily engage with through practice and receiving feedback on the imagery exercises in phase one. However, for a few participants mental imagery remained challenging to engage with throughout the interview, and they required additional prompting and scaffolding to experience any mental imagery.Participants experienced a continuum of mastery over mental imagery. For some, mental imagery across different sensory modalities mental imagery was too hard or inaccessible. Such aspects varied between participants, although several participants found transforming images more difficult than generating new images or inspecting or checking existing mental images. Zadie struggled to change an image of an orange into a frog:OHDo you find it easy to do or hard?ZadieSome of it's a bit hard.OHWhich bits have been hard?ZadieWell, the one you said about the frog.Even with various strategies to support participants' engagement, almost all participants found some aspect of improving concentration was helpful (e.g. suggesting participants close their eyes). Asking both open and closed questions helped participants reflect on their images and develop them further. Scaffolding, which included repeating back descriptions of images, encouraged elaboration. Whilst providing additional prompts and scaffolding generally helped all participants to provide more detailed imagery, it was essential to help some engage with and report mental imagery. Clemency's level of verbal fluency and cognitive skills were somewhat lower than other participants. Whilst she struggled to describe and report her mental imagery to others at points in the interview, she could generate imagery in different sensory modalities relatively easily:OHWhat do the mountains look like?ClemencyThey are white.OHWhy are they white?ClemencyBecause it's got snow.OHThey are very big mountains.ClemencyDon't like snow!OHYou don't like snow?ClemencyCold.Various techniques facilitated the development of mental imagery. Reducing external, environmental distractions and Whilst all participants could engage in mental imagery to some extent, the aspects of mental imagery they found easiest varied. For some this was related to the emotional saliency of an object, whilst others found particular aspects of manipulating images difficult. Other could access mental imagery in specific modalities more easily.A phenomenological approach was used to explore experiences of mental imagery in people with intellectual disabilities. Participants reported rich, detailed mental images, which could be surprising, spontaneous, elicit emotions and experienced across sensory modalities. Their experiences creating, comparing, checking and changing mental images map onto theoretical aspects of mental imagery generation, inspection, maintenance, transformation  or auditory (making the noise of a seagull) cues. Participants shared their internal experiences with the interviewer to build rapport and used mental imagery as a relational tool.Engaging with mental images elicited a range of powerful emotions including joy, disgust and fear, as found in the general population and people undergoing psychological interventions  and experienced a visceral reaction of outrage. Understanding why and when participants engage with various imagery is essential, as it may be erroneously assumed that not engaging with imagery is due to cognitive difficulties. Mental imagery can be emotional (as in this example) or non‐emotional  , this was difficult for some participants with physical disabilities. The individual areas of strength and skills regarding mental imagery required careful exploration with participants, using a curious, non‐judgemental stance to optimise participants' abilities to engage in mental imagery. Several participants found incorporating movement into mental imagery challenging. For others, aspects of imagery transformation (such as in an imagery rescripting exercise) was hard. Understanding which aspects of imagery challenge an individual will be important when exploring mental imagery interventions with people with intellectual disabilities, as is providing practice and feedback on different types of mental imagery exercises.This study employed an inclusive research approach . The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.All authors declare no conflict of interest.


Understanding global patterns of genetic diversity is essential for describing, monitoring, and preserving life on Earth. To date, efforts to map macrogenetic patterns have been restricted to vertebrates, which comprise only a small fraction of Earth’s biodiversity. Here, we construct a global map of predicted insect mitochondrial genetic diversity from cytochrome c oxidase subunit 1 sequences, derived from open data. We calculate the mitochondrial genetic diversity mean and genetic diversity evenness of insect assemblages across the globe, identify their environmental correlates, and make predictions of mitochondrial genetic diversity levels in unsampled areas based on environmental data. Using a large single-locus genetic dataset of over 2 million globally distributed and georeferenced mtDNA sequences, we find that mitochondrial genetic diversity evenness follows a quadratic latitudinal gradient peaking in the subtropics. Both mitochondrial genetic diversity mean and evenness positively correlate with seasonally hot temperatures, as well as climate stability since the last glacial maximum. Our models explain 27.9% and 24.0% of the observed variation in mitochondrial genetic diversity mean and evenness in insects, respectively, making an important step towards understanding global biodiversity patterns in the most diverse animal taxon. This study presents a global map of predicted insect mitochondrial genetic diversity from cytochrome c oxidase subunit 1 sequences. From over 2 million mtDNA sequences, they find a negative quadratic latitudinal gradient in genetic diversity evenness, peaking in the subtropics and correlating with hot, stable environments. These macroecological metrics have long been used to inform conservation and gain insights into mechanisms underlying eco-evolutionary patterns.Resolving global patterns of biodiversity is essential for understanding how life is distributed across the world, and where it is most important to protect it. As yet, global-scale assessments have largely focused on species richness9. In addition to accelerating taxonomy10, DNA barcoding has become a tool in diagnosing conservation status and, more generally, better understanding ecology, evolution, and biogeography13, but see ref. 14. More recently, DNA barcode surveys provide data for the emerging field of “macrogenetics”16, which has the potential to become one of the many approaches used to monitor and protect genetic diversity18. Class III macrogenetic studies, as defined by Leigh et al.19, summarize the geographic distribution of intraspecific genetic variation of a taxonomic group across broad geographic scales and use data from large numbers of species aggregated from public repositories. Typically used to find correlated environmental variables that predict this critical component of biodiversity20, previous class III macrogenetic studies have focused on vertebrate groups, uncovering links between global patterns in intraspecific mitochondrial genetic diversity, species richness, and phylogenetic diversity22, while documenting latitudinal gradients25. They have provided mixed support for the influence of human disturbance on mitochondrial genetic diversity27, and suggest that climate stability27 and species’ range sizes28 affect intraspecific mitochondrial genetic diversity on a global scale.Large-scale georeferenced DNA barcode surveys have great potential beyond their original use and are increasingly used in global studies of biodiversity30, yet existing insect macrogenetic studies have been restricted to regional scales due to the immense effort required to collect, identify, and sequence such a species-rich group36. Studies on the resilience of insect communities to global change38, including biological invasions40, habitat conversion41, and climate change42 arrive at conflicting conclusions. Moreover, comprehensive knowledge of species diversity, distributions, and population dynamics is largely lacking for large insect groups44. These constraints on understanding broad-scale insect biodiversity patterns point to a need for systematic global data syntheses46.This bias in macrogenetic studies towards vertebrates leaves undocumented the bulk of the planet’s animal biodiversity: insects. Insects are vital for maintaining critical ecosystem services and functions48, DNA barcoding and metabarcoding address the severe bottleneck posed by species identification through conventional morphological methods50, and they are viable approaches for rapid, large-scale, global quantification of insect biodiversity51. While being mindful of these limits in our study design and data53, we present a global class III macrogenetic analysis of insect intraspecific mitochondrial DNA patterns. Our study is especially timely given increasing evidence that many insect taxa may be in global decline with respect to occurrence, local richness, abundance, and biomass60.Despite their known limitations15. Therefore, it is important to note that while mtDNA has useful properties12, mtDNA diversity patterns are impacted by multiple processes that distort the patterns shaped by phylogeographic demographic histories, including selection, coalescent variance, and mutation rate variation across taxa64. While taking these complex dynamics into consideration, sampling the mitochondrial genetic diversity of thousands of taxa per locale is a promising initial step towards understanding an important component of biodiversity at global spatial scales66.Nearly all class III macrogenetic studies of animal taxa are based on mitochondrial DNA (mtDNA) sequence data, by far the most abundant type of sequence data in public repositories8. Leveraging this resource, we compiled and analyzed the largest animal macrogenetic dataset ever assembled: 2,415,425 globally distributed and georeferenced mtDNA sequences  for 98,417 operational taxonomic units (OTUs) within the class Insecta. We used these data to generate a global map of insect mitochondrial genetic variation using the commonly used genetic diversity mean (GDM) and a new measure we adapted from macroecology: genetic diversity evenness (GDE). While GDM describes the average genetic diversity (GD) among species sampled from a spatial unit of arbitrary size , GDE represents the evenness of the distribution of per-species GD measures for all focal taxa that co-occur in the same sampled area67. So far, macrogenetic studies have not quantified variation in per-species GD and are therefore unable to distinguish if the high GDM observed in a geographic region is due to high diversity within most community members, or to the coexistence of a few taxa with extremely high diversity and many low-GD taxa , a rich source of single-locus mtDNA that links quality-controlled genetic data with georeferenced metadata69 and human disturbance70, while increasing with climate stability71. Once these environmental correlates of intraspecific insect mitochondrial genetic diversity are identified based on information extracted from insect sampling efforts across the globe, we use them to predict patterns of insect GDM and GDE in undersampled regions. We discuss and interpret our results in the context of classic biogeographic patterns such as the latitudinal diversity gradients in insect species richness, average and variability in range sizes, and late Pleistocene climate cycles.After calculating these two metrics across all OTUs for each cell, we explore how they correlate with global environmental and geographic variables. If GDM and GDE follow classic global biodiversity trends, we expect GDM and GDE to decrease with latitudeN100 = 245, Fig. 2, low root mean squared error) when predicting trained models to withheld test data  were considered. These cells were distributed heterogeneously across the globe and on every continent except Antarctica .On average, each sampled cell included ten insect orders, 689 OTUs, and 9859 individuals. Regions with both high GDM and high GDE (above the 90th percentile) were found in eastern North America, the North American desert southwest, southern South America, southern Africa, and southwestern Australia , but squared latitude had a negative relationship with GDE across the globe at α = 0.05 . In contrast to GDE, neither absolute latitude (p100 = 0.924) nor squared latitude had a significant correlation with GDM . When considering the top three most-sampled orders independently, we found that squared latitude had a negative relationship with GDE in Diptera  and Lepidoptera , but not in Hymenoptera (p100 = 0.352) , while GDM was not correlated with this binary metric (P = 0.484).Higher GDE values were observed in areas that rarely freeze Figs.  and 4c. r > 0.75), we retained 11 environmental variables describing current climate, variables summarizing climate variation since the last glacial maximum , a habitat heterogeneity metric, a human habitat modification metric, and topographic variables. After removing additional variables that did not contribute substantial predictive power according to projection predictive variable selection (see Methods), we used Bayesian generalized linear mixed models (GLMMs) that account for spatial autocorrelation in the residuals to explain environmental relationships and make predictions73. The resulting GLMMs explained 27.9% of the training data variation in GDM : ) and 24.0% of the training data variation in GDE   and GDM .We found that GDM and GDE covary significantly with current and historical climate, and that both are positively correlated with maximum temperature of the warmest month and climate stability variables Figs.  and 4. W%]) Fig. . When prThe GLMM for GDM included eight variables related to current climate: precipitation seasonality, precipitation of the wettest month (PWM), precipitation of the driest month (PDM), maximum temperature of the warmest month (MTWM), and four variables summarizing climate change since the LGM: temperature trend, temperature variation, precipitation trend, and precipitation variation Fig. . In contThere was no residual spatial autocorrelation in the final GLMMs Table , and resWe then used the best-fit GLMM to predict and map the global distribution of GDM and GDE individually and jointly across the globe, including for unsampled areas Fig. . To prevAreas predicted to have high levels of both GDM and GDE (above the 90th percentile) include eastern North America, the North American desert southwest, southern South America, southern Africa, and southwestern Australia , Hemiptera, and Trichoptera. The remaining 2.8% of OTUs belong to 20 additional insect orders. Although Coleoptera has more described species than the other three megadiverse orders, it comprises less than 10% of OTUs represented in the data, possibly due to the common practice of using Malaise traps in flying insect surveys, where Diptera, Hymenoptera, and Lepidoptera dominate sampling74. Across orders, 74.7% of all OTUs occupied a single grid cell with less than one percent occupying more than 11 grid cells . However, GDM was slightly but significantly lower in the full dataset .To investigate the influence of the three most prevalent orders  we removed these orders from the full dataset and reanalyzed patterns of GDE and GDM. Using Welch’s unequal variance t-tests, we found no significant difference in GDE estimates between the full dataset and the dataset with the most prevalent outliers removed  may be a notable exception, as current estimates of species richness show a latitudinal gradient similar to GDE with highest richness at mid-latitudes82. However, when we fitted quadratic correlations to the three most common orders separately, Hymenoptera was the only taxon with the two genetic diversity (GD) metrics that did not match the general trend  that peaks at subtropical latitudes and decreases near the equator and towards the poles Fig. . Howeverend Fig. .85. However, many confounding factors could affect how species diversity metrics relate to GDM and GDE, and these factors may have both positive and negative effects, leading to large variation in the direction and strength of species genetic diversity correlations86, especially at a global scale in such a large taxonomic group such as insects. Sampling biases, especially for the overrepresented North American and European regions may also influence this relationship by overfitting models towards patterns present in these regions, although we find no evidence of a correlation between sampling effort and the two GD metrics in our data  and the lack of an overall correlation with GDM suggests a departure from expectations of species genetic diversity correlation predictions, given the expected negative linear correlation of species richness and latitude20, amphibians23, and fishes22. Why would GDE be lower in areas like the wet tropics where the species diversities of most insect groups reach their peaks88? Rapoport’s Rule, the tendency for species’ range sizes to increase with increasing latitude90, might partially explain this result if species with larger ranges tend to harbor greater genetic diversity92. This expectation has recently been observed empirically28, as well as investigated in a theoretical macrogenetic context whereby per-species GD relates to species’ ranges following a power law20. If processes underlying Rapoport’s Rule operate in the two large insect orders Diptera and Lepidoptera, coalescent times among sampled individuals for larger-ranged species at higher latitudes are expected to be older and therefore yield consistently higher values of per-OTU GD that aggregate to higher GDE within grid cells93. This expectation should hold even if species’ ranges are larger than our chosen 193 × 193 km grid-cells and if subdivision exists within the range of a species95. Furthermore, the inflation of GD in a larger portion of OTUs within a grid-cell serves to increase evenness (GDE) by bridging the difference in GD between high GD and low GD OTUs within the sampled assemblage. This should also lead to higher GDM, but the presence of OTUs with extremely high or extremely low GD are more likely to lead to more statistical noise for the calculation of GDM than GDE. Although we do not find a significant correlation between latitude and GDM, we acknowledge that the positive correlation between GDE and GDM may contain some signal of an increase in GDM with latitude , where GDM increases with PWM, while GDE decreases. The former corresponds with wet, hot regions, while GDE is highest where it is arid and hot , results from climates that have remained stable since the LGM Fig. . Likewisot Figs. .102. Insect diapause is thought to provide this adaptive tolerance to wider abiotic conditions and may result in larger and more uniform range sizes across an assemblage103. If there is a positive relationship between range size and GD92, this could provide a possible mechanistic relationship that connects Rapoport’s Rule and the more uniform genetic diversities found in the subtropics. In this case, increasing GDE with latitude may be driven by uniformly larger range sizes that result from greater physiological tolerances in harsher environments. While this is consistent with both GDM and GDE being most strongly associated with the seasonally hot conditions (MTWM) found in the subtropics  and high long-term climate stability  is reflected by predicted hotspots in the most long-term stable and least seasonal tropical or subtropical forest habitat  communities to have elevated GDE under ecologically neutral conditions in contrast to non-neutral, or “niche-structured”, conditions. In these specific model-dependent cases, the lower GDE in communities assembled via environmental filtering is likely caused by increased genetic diversity in hyper-dominant species with stronger local ecological adaptation. In line with this process-explicit modeling, our observation of GDE increasing from the tropics to the subtropics shows that equatorial insect communities may have stronger, local niche-structured mechanisms  than subtropical temperate insect communities. This would be consistent with the idea of stronger niche conservatism in the tropics108.Areas with higher levels of GDE could also potentially emerge from different points along the continuum of community assembly110. These models will be especially valuable in revealing the underlying mechanisms of unexpected correlations found here and in other macrogenetic studies111.While these are some of the many hypotheses emerging from our study, the correlative approaches we use are a crucial first step to developing a better understanding of the processes underlying biodiversity. To more directly test such hypotheses, process-explicit models, which can uncover causal factors that drive biodiversity patterns as well as discriminate among the processes that do not, will be an important next step114. High genetic diversity may facilitate adaptation to changing climates, emerging diseases, and pollutants: three (of many) potential drivers of the “insect apocalypse”58. In addition, genetic diversity contributes to the diversity and stability of species interaction networks by affecting niche space and competition115, community structure116, and network complexity117. At larger ecological scales, insect genetic diversity may reflect ecosystem function and structure as reliably as other traditional macroecological metrics such as species richness118. It can also augment the resilience of ecosystems that provide continuing services for humankind119, such as disease management, curbing the spread of invasive plants, aiding sustainable agriculture, pollinating food crops, and controlling pests 120.While mtDNA genetic polymorphism is only one component of genome-wide genetic diversity, the latter is critical to the survival of insects and their complex interactions with other organisms121. For well-studied systems, shifts in GDM and GDE may reflect the loss of rare species with less genetic diversity or community shifts toward wide-ranging taxa, including invasive species, and could thus be used in long-term monitoring schemes123. Although large-scale data curation efforts are underway124, the spatiotemporal resolution of genetic sampling currently available does not permit rigorous assessment of how humanity affects insect GD at a global scale. A concerted increase in sampling effort, especially in the data-poor regions we identify, will likely make this feasible in the not-too-distant future.While the metric of global human modification we considered did not significantly correlate with GDM or GDE, there are many facets of anthropogenic disturbance acting at different spatial scales that are difficult to summarize in a single metric12, yet relying on a single-locus marker has drawbacks. Notably, the genetic diversity that mtDNA captures is from a single draw from the stochastic coalescent process63, and due to the lack of recombination, patterns of mitochondrial diversity can be impacted by selection63. Moreover, while a large fraction of insect taxa are infected with Wolbachia and other endosymbiotic bacterial parasites that can be in linkage disequilibrium with mitochondria and act as potent selective agents affecting mtDNA diversity127, a survey of Wolbachia infections in BOLD find that Wolbachia COI is present in only 0.16 percent of cases128. Furthermore, the pattern of genetic diversity at any single locus is ultimately impacted by multiple processes  rather than any one process alone129. For example, despite the likelihood for linked selection and high coalescent variance to distort mtDNA diversity patterns, mtDNA data routinely retain key features of species-specific demographic and phylogeographic histories133. Lastly, emergent patterns of mitochondrial genetic diversity across assemblages demonstrably recapitulate well-known biodiversity patterns like the latitudinal biodiversity gradient, indicating meaningful biological signals26.It is important to note that both metrics are calculated using mtDNA, which is a single, highly functional, non-recombining locus. Using mitochondrial DNA has many important advantages134 and is generally not sufficient for making detailed inference of demographic history or phylogenetic reconstruction62, sampling the mitochondrial genetic diversity of thousands of taxa per locale with rapidly increasing data availability is a promising first step towards understanding an important component of the biodiversity of assemblages at global spatial scales66, and this will be especially valuable until whole-genome data become more readily available through projects like the Earth BioGenome Project  and GEOME . While taking these important cautions into consideration, we view macrogenetics as a developing field and thus basic expectations regarding observed patterns are still not established. Our study is a step in the direction of establishing this foundational knowledge and suggests avenues for ways to test specific hypotheses.While intraspecific mtDNA diversity has been shown to have a weak, non-significant correlation with whole genome genetic diversity in 38 European butterfly species137  was selected as a genetic marker that can be deployed to study genetic diversity at the macrogenetic scale. We downloaded COI mitochondrial sequence data for insects directly from the BOLD website using the application programming interface . Our initial database comprised 3,301,025 complete insect records before applying a series of quality filters. We used the BOLD database’s OTU assignments , which cluster similar sequences algorithmically and map them against the BOLD database142. After trimming end gaps from sequences, we removed exceptionally long sequences  which contained a large proportion of gaps that negatively impacted alignments and the calculation of summary statistics. In addition, we removed shorter sequences (<400 bp) that the BOLD database uses for BIN identification and may downwardly bias GD estimates. We only retained COI sequences from georeferenced specimens. Sequence alignments were independently performed for each OTU within single sampled geographic raster cells, i.e., grid cells. We used default settings in Clustal Omega (v1.2.3) to align the sequences and visually assessed both a random subset of alignments and alignments with genetic diversity values at the tails of the distribution to check for alignment errors143.The barcoding region of the mitochondrial locus http://www.issg.org/database; accessed 23 May 2020]; Invasive Species Compendium ; Center for Invasive Species and Ecosystem Health ; Invasive Alien species in South-Southeast Asia144; Japan Ministry of the Environment ; European Alien Species Information Network . We identified all species and OTUs present on multiple continents and removed those on the invasive species list from our dataset. While some invasive species may be restricted to single continents, removal of such taxa was not possible given the lack of information on changes in insect range boundaries and species assignments.To reduce the potential impact of invasive species on our analyses, we removed trans-continental invasive species from the dataset using a list of invasive insect species compiled from seven resources: Global Insect Species Database [145. This is most commonly the average genetic diversity or, alternatively, a measure of the allelic richness derived from the total number of unique and/or common alleles of a genetic locus across all taxa within an area146. We used two distinct summaries of the former measure of genetic diversity (GD)—the mean (GDM) and evenness (GDE) of genetic diversity per unit of area. To obtain the GD for each OTU per grid cell, we calculated the average number of nucleotide differences across all pairwise sequence comparisons per OTU per base pair147 (a.k.a. nucleotide diversity). Aggregated across OTUs within each grid cell, GDM is then defined as the average GD among OTUs in each grid cell, following21. Because the distribution of GDM at the grid cell scale was highly skewed towards zero, we performed a square-root transformation to achieve a more normal distribution, consistent with Theodoridis et al.’s21 approach. All subsequent statistical analyses of GDM at the grid cell scale were based on the transformed GDM.Previous global macrogenetic studies focused on spatially defined metrics that summarize genetic diversities calculated across all species sampled from an area of arbitrary spatial resolution150. GDE is then defined as the first-order Hill number of GD across OTUs per grid cell, corrected by sampled OTU richness68:N is the number of OTUs in the assemblage and πi is the GD for a single OTU. Correcting for sampled OTU richness allows for comparison across assemblages of different numbers of OTUs. The numerator of this metric is the exponential of Shannon’s diversity index, which is also referred to as Shannon’s information measure or Shannon’s entropy in the literature151. It is commonly used to describe evenness and variability of species abundances153, and here we follow the approach of Overcast et al.68 by adapting it to do the same for genetic diversities calculated from all species sampled from a particular area.While GDM is a standard metric in the macrogenetic toolbox, GDE is derived from a set of metrics often used in ecological studies of biodiversity. Hill numbers permit direct comparisons of diversity across scales and data types152. The distribution of GD values within an area of low GDE can take a variety of shapes, but the most common in our observed data is markedly L-shaped whereby most OTUs have low or zero GD along with a small number of OTUs with large GD  decreased this bias, with estimates of GD with and without duplicate alleles converging for Ne values greater than ~10e5  three different spatial resolutions, and 2) six different thresholds of minimum OTU sample sizes per grid cell. The spatial resolutions include 96.5 km × 96.5 km, 193 km × 193 km, and 385.9 km × 385.9 km equal-area grid cells using a Behrmann cylindrical equal-area projection, which are 1°, 2°, and 4° longitude at 30°N. We considered a minimum of 10, 25, 50, 100, 150, or 200 unique OTUs per grid cell. We chose the spatial resolution that balanced the average number of OTUs per grid cell, the number of grid cells, the average number of taxonomic orders per grid cell, and variation in the number of OTUs across grid cells . Similarly, to investigate whether per grid cell sampling, i.e., total number of individuals, number of individuals per OTU, and number of OTUs per cell, had an effect on GDE or GDM, we tested for Pearson’s correlations between these quantities  and calculating the summary statistics for each resample , prioritizing variables that represent climate extremes, climate variability, habitat variability, last glacial maximum (LGM) climate stability, and human influence on the environment. We prioritized these classes of variables because the influences of environmental extremes and variability across space and time are more likely to shape local communities than averages156.We aggregated a total of 49 abiotic, biotic, and anthropogenic variables that potentially influence intraspecific genetic diversity in insect communities (Supplementary Table 157. They include maximum temperature of the warmest month (MTWM), minimum temperature of the coldest month (MTCM), precipitation of the wettest month (PWM), precipitation of the driest month (PDM), temperature seasonality, and precipitation seasonality158. The habitat heterogeneity metric was calculated as the standard deviation of the Enhanced Vegetation Index, which was derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) . The human modification variable is a cumulative measure of human modification to terrestrial areas160. Measures of both the historical trend and variability of temperature and precipitation over the last 21,000 years were obtained from Theodoridis et al.21. The specific definitions of these derived metrics include “deep-time climate trend”, the change in climate within each century, averaged across centuries, and “deep-time climate variability”, meaning the standard deviation around the change in climate, averaged across centuries. Low deep time trend values indicate regions with long-term climate stability, while low variability values indicate regions with short-term climate stability. Each variable was aggregated from its original resolution  since the LGM  included in the model. Given this correlation, we acknowledge the redundancy in the statistical tests, but we believe that including two perspectives on the geographical structure of genetic diversity allows for direct comparison with existing patterns in the literature that are not apparent otherwise.In addition, we explored the relationship between GDE and GDM and a binary variable delineating the globe into areas that do or do not freeze, which are areas where the long-term minimum temperature of the coldest month (MTCM) is below 0 °C versus above 0 °C, respectively. These regions correspond with sharp community turnover in birdsWe applied a Bayesian modeling approach to identify the environmental conditions that best explain the global distribution of GDM and GDE in insects. We independently modeled the relationship between the set of 11 uncorrelated, ecologically relevant variables (see above) and per grid-cell GDM and GDE values. To assess the predictive ability of the model, we split the data set into 75% training and 25% testing sets, stratifying the sampling by continent to maximize spatial representation of sampling in both data sets. All model selection and model fitting was performed on the training set, while predictive performance of the best fit model was assessed by predicting the withheld test data set.73. We reduced the number of potential predictor variable combinations from the set of 11 variables with low collinearity using Bayesian regression coupled with projective prediction feature selection. This approach minimizes the number of variables in a simple model while retaining comparable predictive power to a model that includes the full suite of predictor variables162. Computational and statistical limitations due to exploring such a wide variety of variable combinations in a Bayesian context prohibited accounting for spatial autocorrelation in this first step. For each model we used regularizing priors on all slope parameters ) and the error term ). We centered and scaled all variables to a standard deviation of 1 and mean of 0 prior to modeling.We prioritized constructing a simple, interpretable linear model that predicts GDM and GDE across the globe by first reducing the number of potential variable combinations, followed by a Bayesian hierarchical generalized linear mixed model (GLMM) approach that accounts for spatial autocorrelation163. We tested for SAC in the residuals of the resulting simplified models using Moran’s I and 10,000 simulations implemented in the R package spdep v1.1-2164. We detected significant levels of SAC in the residuals of our GDE model  and our GDM model .If residual spatial autocorrelation (SAC) is present, the assumption of independent and identically distributed residuals would be violated, resulting in potentially biased overprecision of parameter estimatesglmmfields v 0.1.4 to model the relationship between the variables and the two GD metrics (GDE and GDM) while accounting for SAC73. SAC is modeled as a random effect with a multivariate t-distribution determining the shape of the covariance matrix. Model parameters were estimated from the posterior distribution using a No U-Turn Sampler166. Further model specifications are provided in the Supplementary Methods. We again tested for SAC in the residuals of these models using the same approach as above. The proportion of variance explained by the models were assessed with Bayesian R2167, modified to account for spatial autocorrelation error. After selecting a model, we used the percentage of prior-posterior overlap to assess the identifiability of parameter estimates relative to the information provided by their prior distributions168. Low overlap between the prior and posterior distribution of a parameter indicates that there is sufficient information in the data to overcome the influence of the prior.Given this presence of SAC, we used a Bayesian hierarchical GLMM implemented in the R package SpatialPack v0.3.0170. This was done for the full data set and independently for the three most sampled orders. We also independently tested the effect of whether an area freezes or not on the two GD metrics using the same modified t-test of spatial association.We tested for the statistical significance of a linear or quadratic relationship between latitude and GDM and GDE while accounting for spatial autocorrelation using a modified two-sided t-test of spatial association, implemented in the R package Using the final models of GDM and GDE, we created maps of the global distribution of insect GD. We used 1000 draws from the posterior distribution to predict terrestrial environments across the globe. We included all continents except Antarctica, which had no observed data and included environments far more extreme than the observed data. We created maps of the median predicted GDM and GDE, along with the upper and lower 95% HDI. In addition, we created bivariate color maps of these prediction intervals for combined GDM/GDE to highlight areas where GDM and GDE vary in similar and different directions.171. Following best practices to avoid extrapolation172, we used the MESS results to mask areas with non-analogous environmental space  on our global prediction maps, indicating areas with high prediction uncertainty.To avoid making poor predictions into areas with environments that are non-analogous to the areas used to train the models, we used multivariate environmental similarity surface (MESS) maps (Supplementary Fig. Further information on research design is available in the Supplementary InformationPeer Review FileReporting SummarySource Data


Direct-to-consumer genetic testing (DTC-GT) is becoming an increasingly profitable private enterprise that provides genetic testing kits directly to consumers. DTC-GT companies advertise themselves as a method for patients to take control of their own health and investigate their risk of diseases and conditions as well as look into their ancestry. The scope of practice of these companies continues to widen offering more services. Consumers may therefore have a relatively poor understanding of the services provided when purchasing these products. The testing methods utilised show some limitations, the consequences of which have the possibility of leading to harm to consumers. The result of the data gathered may instigate the formation of negative stereotypes from the public and reinforce existing ones towards a population that may have already been previously subjugated to unfair treatment. The controversy surrounding how data are utilised further impacts how many may engage in its use. This review aims to provide an overview of the services these companies purport to provide as well as highlight important ethical issues of the service such as quality of information, privacy concerns, negative psychosocial impact and the effect on clinical practice. There are many private companies offering test kits using saliva samples that provide genealogical information screening for specific disease traits. These kits can be easily purchased online, and it has been common to see spikes in purchases during sale times throughout the year. Since 2019, there have been more than 26 million people that have been tested by the four largest direct-to-consumer genetic testing (DTC-GT) companies [Different types of direct-to-consumer genetic tests provide screening for different types of information, these include carrier screening, potential health risk, potential pharmacological intolerance/allergy risk, predisposition to cancer, ancestry and uninterpreted raw genetic data .Data qualityGenetic test kits advertised by DTC-GT companies are marketed and sold as being able to provide consumers with information regarding potential risks for disease. The method most commonly utilised for analysing DNA is single nucleotide polymorphism (SNP)-chip genotyping which demonstrates high accuracy when analysing the presence of common SNPs of disease. Results of genetic testing are compared against genome-wide association studies (GWAS) data which provides information on whether an SNP is statistically associated with traits and diseases. Although disease associations may exist, phenotypic expression of disease may not necessarily occur. An example highlighting this includes the G-174C polymorphism on the interleukin gene. This polymorphism is associated with many diseases including cardiovascular diseases; however, a meta-analysis consisting of a large number of patients demonstrated that its presence had no clinically significant effect on the risk of cardiovascular diseases . The senThe option for customers to download uninterpreted genetic data is offered by some DTC-GT companies following receiving their results. This data can be interpreted by third-party services that use genomic browsers and other sources to assess it and provide carrier status for conditions and additional risk scores for diseases and conditions . These gThe DTC-GT testing highlights potential disease-predisposing variants but may neglect to identify disease-protective factors that may be present. If selective genes are identified to identify potential causal variants whilst neglecting to identify protective factors, skewed data may be collected which has the potential to be exploited. This can be seen with a study aimed at identifying variants associated with obesity in Samoan populations. rs12513649 was a common variant identified amongst Samoan populations highly associated with raised BMI, yet many possessed a further variant present on the CREBRF gene that provided a protective influence against diabetes . FurtherImplications of inaccurate resultsAlthough it may be seen as a positive that many of the consumers taking an interest in managing their own health with DTC-GT, inaccurate or poorly interpreted results may lead to potentially harmful consequences. It is important for healthcare providers to be wary of this as it can consequently lead to unnecessary testing and procedures being performed ,6.Concerns have also been highlighted regarding the genetic markers used to identify risks of specific conditions. This can be seen with the genetic markers used by 23andMe for BRCA which only identifies variants that are common in Ashkenazi Jews. The statistics show that the variants used to identify the condition were present in approximately 2% of Ashkenazi Jewish females and 0.01% of the general population. The results would miss the BRCA variant in approximately 80% of the population . CustomeThe psychological impact of resultsThe possibility of anxiety and depression following experiencing negative test results with little follow-up support is significant. In a study completed, 38% reported they did not consider the possibility of receiving information regarding ill health . ResultsResults of DTC-GT are usually received through email and without the support of medical professionals to help interpret the results. This can lead to anxiety and without proper expertise to interpret the results, this may be unresolved for some time. Lack of medical knowledge and access to counselling poses a significant issue as anxiety levels were seen to be higher in those who had a poorer understanding of results . This anConfidentiality and privacyMany patients decline participation in genomic research due to fears of disclosure of results. Concerns also arise regarding information sharing with pharmaceutical companies and data loss via cybersecurity attacks. A recent study has indicated that 67% of DTC-GT companies provided an insufficient amount of information on how consumer data would be utilised . AlthougThe data protection and privacy legalities have been difficult to find and interpret for consumers when accessing websites providing DTC-GT. A specific area of concern from consumers is not knowing what happens to data in the event of company insolvency. Currently, DTC-GT companies in the United States are currently under no obligation to notify consumers when actioning policy changes of their terms and conditions. This may be concerning to consumers as personal data is being held . Given tThe results of genomic tests undertaken in Aotearoa New Zealand can legally be requested by insurance companies thus impacting the cost of premiums. Genetic counsellors have a professional responsibility to make patients aware that any testing undertaken in clinics may be required to be disclosed to insurance companies. The limited ability of genetic data to provide information on whether genetic data will result in phenotypic changes may be exploited by insurance providers. The use of genomic data of traits similar amongst specific ethnicities may lead to genomic discrimination amongst populations .Other countries such as the United States, United Kingdom, and Australia have implemented measures to protect patients from insurance provider discrimination based on genetic results. The Genetic Information Non-discrimination Act 2008 developed in the United States provides protection for its citizens. Data protection laws in the United Kingdom protect patients from mandatory disclosure of genetic test results to insurance companies. In 2019, Australia introduced the Moratorium on Genetic Tests in Life Insurance preventing the use of predictive genetic testing for insurance purposes . The allInformed consentPoor consumer education prior to testing is a concerning issue. A lack of transparency relating to the accuracy of testing, which demographics are covered, penetrance of diseases, privacy of results and storage of data is apparent. A significant proportion of patients reported not considering receiving a result implicating ill health, thus further demonstrating the lack of understanding prior to testing . Test kiHealth improvement following resultsA common reason for undertaking genetic testing was the consumers desire to improve their overall health if they were at higher than average risk of illness than the general public . GreaterRegardless of the above claims from consumers, no statistically significant change in fat intake or exercise in consumers at short term (three months) or long term (one year) follow ups was seen. Alongside this, consumers demonstrated no significant difference in their undertaking of health screening to monitor their health. This was also seen with those receiving genetic testing result showing an increased risk of cancer not being statistically significantly more likely to engage in cancer screening than the general population .In terms of managing risk for other conditions, such as type 2 diabetes, it has been suggested that weight management of individuals in the population would be enough to negate the risks of expression of the disease making the need for DTC-GT negligible . As mostIncreased burden on healthcareDTC-GT companies do not offer pre- or post-test genetic counselling leading to poorly informed patients seeking support from elsewhere. This has led to the development of online forums and support groups for consumers to share their results in the hope of receiving support with their results with regards to health implications and support for those who have newly found family members via the ancestry genetic testing. Support in these forums is provided by fellow consumers lacking in medical knowledge which may further lead to confusion and distress . Given tDTC-GT has been presented as a method for patients to manage their future health by offering predictions of potential diseases yet comes with major limitations. The potential for deterioration of the mental health of consumers is significant and the absence of any notable lifestyle changes following receiving results points towards the limited real-life applicability of tests. Transparency with regard to data accuracy, validity, and use needs to be addressed across many companies. Clarity and stringency of laws surrounding genetic data need to be provided by many countries. New Zealand laws at present, fail to instate reasonable protection against genomic discrimination resulting in justified fears surrounding disclosure of genetic data. With advocacy groups such as AGenDA and BCAC fighting for change, some of these limitations may be addressed in the near future.


Fufang Honghua Buji (FHB) granules, have proven efficacy against vitiligo in long-term clinical practice. However, its major active chemical components and molecular mechanisms of action remain unknown. The purpose of this study was to confirm the molecular mechanism of FHB’s therapeutic effect on vitiligo utilizing network pharmacology, molecular docking, and molecular dynamics simulation prediction, as well as experimental verification.Traditional Chinese Medicine Systems Pharmacology (TCMSP) and HERB databases were used to obtain the chemical composition and action targets of FHB. Online Mendelian Inheritance in Man (OMIM), DrugBank, DisGeNET, GeneCards, and Therapeutic Target Database (TTD) databases were applied to screen for vitiligo-related targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed through the Matascape database. Molecular docking and dynamics simulation methods were for the analysis of the binding sites and binding energies between the FHB’s active components and the targets. Finally, a vitiligo mouse model was created, and the therapeutic effect and molecular mechanism of action of FHB were validated using enzyme linked immunosorbent assay (ELISA), western blot (WB), and quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Additionally, hematoxylin-eosin staining (HE) and blood biochemical assays were conducted to assess the biosafety of FHB.in vivo safety evaluation experiments also demonstrated the non-toxicity of FHB.The screening of chemical composition and targets suggested that 94 genetic targets of FHB were associated with vitiligo. The bioinformatics analysis suggested that luteolin, quercetin, and wogonin may be major active components, and nuclear factor-kappa B p65 subunit (RELA), signal transducer, and activator of transcription (STAT) 3 and RAC-alpha serine/threonine-protein kinase (AKT) 1 may be potential targets of FHB-vitiligo therapy. Molecular docking and dynamics simulation further demonstrated that luteolin, quercetin, and wogonin all bound best to STAT3. Through experimental verification, FHB has been demonstrated to alleviate the pathogenic characteristics of vitiligo mice, suppress the JAK-STAT signaling pathway, reduce inflammation, and increase melanogenesis. The FHB exerts anti-inflammatory and melanogenesis-promoting effects via the effect of multi-component on multi-target, among which the JAK-STAT pathway is a validated FHB-vitiligo target, providing new ideas and clues for the development of vitiligo therapy. GeneticCarthamus tinctorius L.), Fructus Psoraleae , and puncture vine (dried ripe fruit of Tribulus terrestris L.) being the most important therapeutic components. Safflower is commonly used to promote blood circulation and cure blood stasis. The isolated safflower yellow (CY) from safflower has been proven to effectively reduce whole blood viscosity, plasma viscosity, and erythrocyte aggregation index  has gained popularity as a complementary alternative medicine around the world, with many herbal formulas successfully treating diseases such as cancer, diabetes, and novel coronavirus –14. TCM on index , and safon index . Psoraleon index , 19. Trion index , and it on index . DespiteTCM formulas have a complicated chemical composition with multiple active targets. Network pharmacology, which is based on systems biology theory, employs network analysis and other techniques to reveal the complex network relationships between drug targets and diseases, providing a new approach to predicting the molecular mechanisms of TCM formulas, including multiple active components, contributing targets, and involved pathways . The sim22.1Carthamus tinctorius L.), puncture vine (dried ripe fruit of Tribulus terrestris L.), dark plum (Prunus mume Sieb. et Zucc.), catnip (Nepeta cataria L.), Danshen , Dangshen (the dried root or rhizome of Codonopsis pilosula (Franch.) Nannf.), siberian cocklebur fruit (the fruits of Xanthium sibiricum Patr.), licorice , peach seed (Prunus persica L. Batsch), Danggui (the root or rhizome of Angelica sinensis (Oliv.) Diels), milkvetch root  Bunge.), Daxueteng (the liana stem of Sargentodoxa cuneata (Oliv.) Rehd. et Wils.), Saposhnikoviae Radix (the root or rhizome of Saposhnikovia divaricata (Trucz.) Schischk.), Herba Siegesbeckiae , Fructus Psoraleae , Heshouwu  Harald.), and magnetic powder (Fe3O4) were purchased from Shanghai Hongqiao Chinese Medicine Beverage Co., Ltd. Carboxymethylcellulose Sodium, hydroquinone (HQ) were bought from MACKLIN reagent, IL-6 mouse ELISA kit (030311WL202680304), TNF-α mouse ELISA kit (030311WL104840304) and TYR mouse ELISA kit (030311WL204410304) were from Jianglaibio,STAT3(bs-1141r), IL-6(bs-6309r), and TNF-α(bs-10802r) antibodies were procured from Affinity Biosciences, formalin, 4% Paraformaldehyde Fix Solution, RNA extraction solution was bought from Solarbio, and NovoScript Plus All-in-one 1st Strand cDNA Synthesis SuperMis (gDNA Purge) kit and NovoStart SYBR qPCR SuperMix Plus kit were purchased from Novoprotein, China. CCK8 (C0038) kit and H2O2 (9011M2114540) were purchased from Beyotime.Traditional Chinese medicine (TCM) materials including safflower .2.2FHB granules are an oral TCM formula used in clinical treatments of vitiligo at the Shanghai Skin Disease Hospital. The TCM materials of Fufang Honghua Buji (FHB) granules - i.e., carthami flos (Carthamus tinctorius L.), psoraleae fructus , tribuli fructus (Tribulus terrestris L.), salviae miltiorrhizae radix et rhizoma , persicae semen (Prunus persica (L.) Batsch), angelicae sinensis radix (Angelica sinensis (Oliv.) Diels), glycyrrhizae radix et rhizoma , codonopsis radix (Codonopsis pilosula (Franch.) Nannf.), polygoni multiflori radix (Polygonum multiforum Thunb.), magnetitum (Fe3O4), xanthii fructus (Xanthium sibiricum Patr.), saposhnikoviae Radix (Saposhnikovia divaricata (Trucz.) Schischk.), schizonepetae herba (Schizonepeta tenuifllia Briq.), siegesbeckiae herba , mume fructus (Prunus mume (Sieb.) Sieb. et Zucc.), stagentodoxae caulis (Sargentodoxa cuneata (Oliv.) Rehd. et Wils.), and astragali radix  Bge.) were mixed in the ratio of 1.7: 1.7: 1.1: 1.1: 1.1: 1.1: 1.1: 1.1: 1.1: 1.1: 1.1: 1.1: 2.2: 2.2: 2.2. Then, the mixture was decocted with 10-fold weight of water for 2h, and was subsequently decocted with 8-fold weight of water for 1h. After two decoction processes, the filtrates after filtration by sterilized gauze were combined and were left to set for 24 h. After that, the supernatant was taken for concentration and evaporation using a rotatory evaporator. Finally, the concentrated extract was added with appropriate amounts of excipients (sucrose and dextrin with 2: 1.25), stirred well, and dried into granules. In our experiment, due to the low concentration of the granules after brewing, we chose to gavage mice directly with the aqueous concentrated extract of FHB to achieve sufficient dosing concentration as well as to facilitate absorption in mice.2.3https://old.tcmsp-e.com/tcmsp.php) database and Herb database (http://herb.ac.cn/), and screened was also based on oral bioavailability (OB) and drug-like index (DL). The components meeting both OB>30% and DL≥0.18 were selected as potential active compounds  , and converted into the Official Gene Symbol of Homo sapiens. Vitiligo-related targets were obtained from the OMIM database (https://www.omim.org/), DrugBank database (https://www.drugbank.com/datasets), DisGeNET database (https://www.disgenet.org/), GeneCards database (https://www.genecards.org/) and TTD database (http://db.idrblab.net/ttd/) by searching “vitiligo” as the keyword and removing duplicate and false positive genes. FHB targets and vitiligo-related targets were processed using the Venny 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/) online tool, and the intersection target genes of the two (FHB-vitiligo targets) were collected as the potential targets of FHB for vitiligo treatment.Target information of active compounds in FHB was collected from TCMSP and Herb databases. All FHB targets collected were combined and de-duplicated, then corrected on the Universal Protein database (2.5https://cn.string-db.org/), set the condition as human (homo sapiens), selected data with combinescore≥0.9 to imported into Cytoscape 3.7.2 (https://cytoscape.org/), and constructed the PPI network model. The Degree values of the topological parameter in the network were used to identify the core target genes in the network.To further investigate the interaction of FHB involved in vitiligo-related targets, we imported the FHB-vitiligo targets into the STRING database (2.6https://metascape.org/gp/index.html#/main/step1) was utilized to perform enrichment analysis of FHB-vitiligo target genes. Metascape integrates KEGG pathways, GO biological processes, reactant gene sets, classical pathways, transcriptional factor targets, and other tools to annotate biological processes and pathway analysis. All genes are used as enrichment backgrounds. In addition, the systematic data are well-timed. A threshold of p < 0.05 was used to identify key GO and KEGG pathways.Metascape , and the 3D structure of the target protein was obtained from the PDB database (https://pubchem.ncbi.nlm.nih.gov/). These files had been saved in PDB format. In AutoDock4, the active compound protein files were set as follows: water was removed and replaced with hydrogen, and the protein was designated as a receptor and stored as a PDBQT protein receptor file. The protein structures’ water molecules and small molecule ligands were removed using Pymol2 software, and the data were then imported into AutoDockTools1.1.2 for pre-processing of dehydration reaction and hydrogenation. To examine the junctions and activities of targets and FHB molecules, molecular docking was performed in AutoDock vina1.1.2.Based on the results of a previous network pharmacology screening, the 2- dimension (2D) structures of potential active compounds in FHB were downloaded from the PubChem database  and isothermal isobaric system (NPT), and then molecular dynamics simulations were performed for 30 ns at room temperature and pressure.2.102.10.1Hydroquinone (HQ) was used in our experiment to induce vitiligo in mice. The back hair of all experimental mice was shaved over an area of 3cm × 2cm.The mice were randomly divided into 5 groups, 5 mice each group (1): Control group: 1% Carboxymethylcellulose Sodium was applied to the shaved area on the back of the mice. (2) Hydroquinone (HQ) group: 5 mg 3% HQ ointment was evenly applied to the shaved area, and 0.4 ml of pure water was gavaged. (3) HQ+0.8g/kg FHB group: 5mg 3% HQ ointment was evenly applied to the shaved area, followed by the gavage of 0.4ml FHB (0.8g/kg). (4) HQ+ 2.4g/kg FHB group: 5mg 3% HQ ointment was evenly applied to the shaved area, and then 0.4ml FHB (2.4g/kg) was gavaged. (5) HQ+7.2g/kg FHB group: 5mg 3% HQ ointment was evenly applied to the shaved area, followed by the gavage of 0.4ml FHB (7.2g/kg). All the groups were administered once a day for 60 days. On day 60, the vitiligo area of each group  was imaged using a digital camera, and was evaluated according to the previous protocol: 0 points were labeled for the absence of depigmentation 0%; 1 point was labeled for 0 > 5%; 2 points were labeled for > 5–25%; 3 points were labeled for> 25–50%; 4 points were labeled for > 50–75%; 5 points were labeled for > 75–100% (2.10.24 cells) per well. The control group was incubated with 1640 medium and the H2O2 group was incubated with different concentrations of H2O2 solution  for 2h, 4h, 6h, and 8h respectively. The viability of B16 cells was assayed at different periods using the cck-8 method.B16 melanoma cells were purchased from the ATCC cell bank. To construct vitiligo model cells, cells were inoculated into 96-well plates at 100 μl  were used to treat vitiligo B16 cells (200μmol H2O2 for 6 hours). After 24h-incubation of FHB, the viabilities of vitiligo B16 cells were detected using cck-8. The control group was incubated with a mere 1640 medium for 30 h, and the H2O2 group was first incubated with 200μmol H2O2 for 6 hours, and then incubated with a mere 1640 medium for 24h.To examine the 2.10.3Blood samples collected from the orbits were allowed to stand for 1 h at 4°C and then were centrifuged (1800 rpm/min) for 5 min at 4°C. The supernatant was collected and used for ELISA. IL-6, TNF-α, and TYR protein expression levels were detected using an IL-6 mouse ELISA kit, TNF-α mouse ELISA, kit, and TYR mouse ELISA kit.2.10.4The collected skin samples were fixed with 4% formalin solution, followed by melanin staining performed by Wuhan Service Technology Co., Ltd. 200 × microscopy was used to observe the pathological changes in the dorsal lesions, which were imaged using CaseViewer 2.2 scanning and viewing software.For immunohistochemical staining analysis, the skin of the dorsal lesions was collected, fixed in 4% paraformaldehyde, and then immunohistochemical (IHC) staining was performed to analyze the expression of IL-6, TNF-α, and p-STAT3. Antibodies used for immunohistochemical staining included IL-6, TNF-α, and p-STAT3. The expressions of IL-6, TNF-α, and p-STAT3 were quantified based on positive areas within each square millimeter of the epidermis. The positive areas band intensities were quantified using Image J software . Three sections per group were used for analysis.2.10.5The total RNA of vitiligo skin tissue on the back of mice was extracted using an RNA extraction solution according to the manufacturer’s instructions. According to the instructions of the NovoScript Plus All-in-one 1st Strand cDNA Synthesis SuperMis (gDNA Purge) kit, 1μg of RNA was utilized in reverse transcriptase reaction to gain cDNA.-ΔΔCT. The mRNA levels of tested genes were normalized glyceraldehyde-3-phosphate dehydrogenase (Gapdh) as an internal reference. The qRT-PCR experiment was conducted in biological triplicate for each group.The expression of Jak1, Jak2, Sta1, Stat2, Stat3, TNF-α, IL-6, and Tyr was investigated using RT-PCR. The primer sequences of the above genes are listed in 2.10.6Cells and tissues were homogenized in a cell lysis reagent, lysed on ice for 30 minutes, and then centrifuged at 16000 g at 4°C for 5 minutes. A BCA protein assay kit was used to detect the total protein concentration of each sample. SDS-PAGE gels were used to grade the proteins, which were then blotted onto nitrocellulose membranes. Subsequently, nonspecific binding was blocked in TBST  with 5% skim milk powder at 25°C for 1 h. The membranes were then incubated with the indicated primary antibodies (p-STAT3) at 4°C. Afterward, the membranes were washed three times with TBST and inoculated with a secondary antibody. Visualize protein bands using the Bio-Rad Chemi Doc XRS+ imaging system. Band intensities were quantified using Image J software . All Western blot assays were performed in triplicate.2.10.7Twenty mice were randomly divided into Control and FHB groups, with 10 mice in each group. To make 0.75g/ml of FHB aqueous extract, 0.3g of the dried FHB aqueous extract powder was weighed and combined with 0.4 ml of pure water. The administration group was given 0.5 mL of 0.75 g/mL FHB per day and the blank group was given the same volume of saline for 14 days. After treatment, mice were euthanized, and the blood of the mice was collected. The plasma was sent for a hematology survey (n = 5), and the serum was separated for biochemistry analysis (n = 5). The main organs were taken from the mice and processed into sections for HE staining. 200 x microscope to observe the pathological changes of each organ.2.11GraphPad Prism 8.0 software  was used for analysis and graphing. The data are presented as the mean standard ± standard error of the mean. To compare various groups, a one-way analysis of variance (ANOVA) was utilized. The statistical significance level was set at p<0.05.33.1The chemical components of FHB were gathered from the TCMSP and Herb databases, and the screening conditions were set as OB ≥ 30% and DL ≥ 0.18. After removing repeated and false-positive components and targets, a total of 291 active components and 349 potential FHB action targets were predicted 2. To se3.2To create a PPI network, 94 potential FHB action targets for vitiligo were uploaded to the STRING database, and the system was configured as follows: selecting “Homo sapiens” in the species column, choosing “Evidence” in the network edge column, and setting the confidence level to > 0.9. A total of 94 target nodes and 296 lines were collected in the PPI network of FHB-vitiligo targets, showing the intricate interconnection between these targets  and the top three FHB-vitiligo targets . With -7.4, -7.3, and -7.5, respectively, luteolin, quercetin, and wogonin all had the strongest binding affinity to STAT3 protein Table 3.3.6The molecular dynamic simulation was performed to further confirm the binding abilities of STAT3 to luteolin, wogonin, and quercetin. RMSD curves indicated fluctuations in protein conformation. As shown in In addition, SASA analysis was performed to detect the degree of exposure of the receptor to surrounding solvent molecules during the simulation. The solvent-accessible surface area of STAT3-wogonin, STAT3-luteolin, and STAT3-quercetin complexes gradually decreased throughout the simulation, indicating that the bindings between them are gradually increased  ointment was applied to the shaved area on the back of the mice to induce the vitiligo mice model. As seen in The results of Masson-Fontana staining showed that after 60 days’ treatment, the epidermis of mice in the control group had a large number of melanin granules in hair follicle cells with no hyperplasia, whereas mice in the vitiligo model group had significantly fewer melanin granules, and the epidermis of vitiligo mice was hyperplastic and the number of hair follicles was reduced  -mediated inflammation is important in the development of vitiligo, and CHE and TYR are molecules related to melanin synthesis. As shown in In addition, we used IHC to further investigate the expression of inflammatory markers IL-6 and TNF-α in the skin tissues. In comparison to the control group, HQ-induced vitiligo mice had a significant increase of IL-6 and TNF-α in both skin tissues and melanocytes, but FHB therapy can effectively decrease them , a crucial inflammatory chemokine in vitiligo, as well as to stimulate melanin synthesis in cell and zebrafish models , 28. Woge damage . As an ae damage –36. ThesRM) cells, which may make repigmentation not durable  can bind to specific JAKs(Janus kinases) and activate downstream STAT  proteins’ phosphorylation and dimerization  tend to be reduced in expression in vitiligo models and clinical, and the expression of cholinesterase (CHE) may increase , 53. SkiThis study still has several limitations. First, some chemical components and targets have not yet been reported in the network pharmacology database, while vitiligo-related targets are continually being updated, so this study may not be completely accurate. Second, we chose representative STAT3 target genes and relevant JAK-STAT pathways for pharmacological experimental validation, but we did not test the inhibitory effects of FHB on MAPK, PI3K/Akt, NF-κB, HIF-1α, and other inflammatory pathways associated with vitiligo and predicted network pharmacological results. Furthermore, though we identified luteolin, wogonin, and quercetin as probable key chemicals in FHB, they may not be equivalent to FHB, and the synergistic effects of the three key compounds still require experimental validation.5in vivo experiments further revealed that FHB could inhibit STAT3’s expression, phosphorylation, and dimerization to exert an anti-inflammatory and melanogenesis-promoting effect, and treat vitiligo by downregulating the JAK-STAT signaling pathway. Our study first combined network pharmacology, molecular docking, Molecular dynamics simulation, and experimental verification to demonstrate that FHB could significantly reduce the expression of JAK-STAT pathway genes, alleviate inflammation and enhance the secretion of melanogenesis-related factors TYR to promote melanin pigmentation, which may support FHB as an alternative therapy for the treatment of inflammation and vitiligo.In this study, we discovered that FHB had therapeutic effects on vitiligo by modulating various components, targets, and pathways. Luteolin, wogonin, and quercetin are key active components of FHB, which may act on targets like RELA, AKT1, STAT3, MAPK14, TNF-α, and IL-6 to regulate pathways including NF-κB, PI3K/Akt, and JAK-STAT signaling pathways, thereby exerting therapeutic effects. The results of molecular docking and Molecular dynamics simulation demonstrated that the main components and key target proteins predicted by network pharmacology bind well. The The original contributions presented in the study are included in the article/The animal study was reviewed and approved by Ethics Committee of Shanghai Skin Disease Hospital.XL, FM, and RX conceived and designed the article; JY and HH performed experimental work. ZT, HP, ZC, and QZ reviewed and edited the manuscript. All authors contributed to the article and approved the submitted version.


Activation of signal transducer and activator of transcription 3 (STAT3) has been identified as a key cardioprotective signal not only in animal studies but also in humans—in animals, STAT3 is causally involved in cardioprotection. In response to late ischemic conditioning, canonical function of STAT3 activation upregulates the expression of cardioprotective and anti-apoptotic proteins. In its non-canonical function, STAT3 is activated during ischemic conditioning and is part of the cardioprotective cytosolic survival activating factor enhancement pathway. Activated STAT3 is imported and localized to the mitochondria. Mitochondrial STAT3 stimulates the activity of mitochondrial electron transport chain complex I, reduces mitochondrial reactive oxygen species production and mitochondrial permeability transition pore opening. Finally, two novel aspects of STAT activation in cardioprotection are discussed: a genetic variance of the STAT encoding region as a potential primordial confounding variable for cardioprotection, and the cardioprotective potential of sodium–glucose cotransporter 2 inhibitors through STAT3 activation. In addition to rapid reperfusion and current therapy there is still a need for cardioprotection to reduce morbidity and mortality in patients with acute myocardial infarction. In experimental settings, there are mechanical and pharmacological interventions that reduce myocardial infarct size. The strongest and most robust cardioprotective intervention is ischemic conditioning, which is effective in all species tested so far, including humans , 52. RedCurrently, the underlying myocardial signal transduction of cardioprotection , 45 can Outside the nucleus, the non-canonical function of STAT3 plays a unique role in acute cardioprotection: in contrast to all other cardioprotective signals, STAT3 activation is consistently not only associated with the reduction of infarct size by all ischemic conditioning procedures, but also causally involved in cardioprotection in all species tested to date , 67, 69—The common intracellular target of all cardioprotective pathways, including the SAFE pathway, are mitochondria . As suchimport of STAT3 mediated through chaperone-like activity of a complex I subunit protein—the protein of the gene associated with retinoid interferon-induced cell mortality 19  production was, thus, ruled out [Phillips et al. had questioned the functional relevance of mitochondrial STAT3 by quantitative biochemical analyses: the abundance of mitochondrial STAT3 compared with respiratory chain proteins was low, with a ratio of electron transport complex proteins to STAT3 of ~ 10uled out . Howeveruled out . Cardiomuled out  uled out . In isoluled out . The biouled out , indicatuled out   and 50% (estimated from nuclei data) , 102. In5) [Based on the findings discussed above, it is reasonable to assume that mitochondrial STAT3 plays a critical role in cardioprotection Table . Again, 5) , so a re5) , detecti5) . Further5) . OverallIn conclusion, the precise function and importance of mitochondrial STAT3 during cardioprotection is still unclear. Finally, to what extent the acute cardioprotective effect is mediated by cytosolic STAT3 or mitochondrial STAT3 activation remains open.Indeed, there is even evidence from the human myocardium that STAT is associated with cardioprotection by ischemic conditioning. In left ventricular biopsies, taken at early reperfusion after cardioplegic ischemic arrest from patients undergoing bypass surgery , the actOssabaw minipigs, a particular strain of minipigs, are characterized by a genotype associated with a thrifty phenotype. Like humans, they develop a metabolic syndrome when fed a hypercaloric, atherogenic diet and consequently coronary atherosclerosis and occasional myocardial infarction , 118. ThThe neutral results of this prospectively designed experimental study in the Ossabaw minipigs are similar to the neutral results of several larger all-comer randomized controlled trials on RIC in patients undergoing interventional reperfusion of myocardial infarction  or cardiSodium–glucose cotransporter 2 (SGLT2) inhibitors—also known as gliflozins—are a class of drugs originally developed to treat type 2 diabetes via inhibition of the sodium–glucose transport protein 2 in the kidney . Among aRecently, also other compounds have been described that activate STAT3 and are causally involved in cardioprotection under experimental conditions. The anabolic steroid nandrolone decanoate  and dexmSTAT3 plays an important role in cardioprotection, also in the human heart. In animal models, there is evidence of mitochondrial STAT3 involved in mitochondrial function. The assumed causal relationship between mitochondrial STAT3 and cardioprotection is based on only one study in pigs. Data from human myocardium on mitochondrial STAT are lacking. There is a primordial non-responsiveness to cardioprotection in pigs which involves STAT3. Combination therapies that acutely activate STAT3—possibly mitochondrial STAT3—through different pathways could therefore be particularly effective, as they could bypass possible blockades upstream of STAT3. The timing of STAT activation seems to be relevant for therapeutic approaches. Acute activation and the non-canonical function of STAT3 are cardioprotective, subacute activation of canonical STAT3 function in late preconditioning is also cardioprotective. However, chronic activation of canonical STAT3 function may be more detrimental than beneficial.


Lateolabrax maculatus) has a broad latitudinal distribution range along the marginal seas of the Northwest Pacific and thus provides an excellent teleost model for population genetic and climate adaptation studies. We generated over 8.57 million SNP loci using whole‐genome resequencing from 100 samples collected at 14 geographic sites (five or ten samples per site). We estimated the genetic structure of the sampled fish and clustered them into three highly differentiated populations. The genetic differentiation pattern estimated by multivariable models combining geographic distance and sea surface temperature differences suggests that isolation by distance and isolation by environment both have significant effects on this species. Further investigation of genome‐wide evolutionary signatures of climate adaptation identified many genes related to growth, muscle contraction, and vision that are under positive natural selection. Moreover, the contrasting patterns of natural selection in high‐latitude and low‐latitude populations prompted different strategies of trade‐offs between growth rate and other traits that may play an essential role in adaptation to different local climates. Our results offer an opportunity to better understand the genetic basis of the phenotypic variation in eurythermal fishes inhabiting different climatic regions.Consideration of the thermal adaptation of species is essential in both evolutionary biology and climate‐change biology because it frequently leads to latitudinal gradients of various phenotypes among populations. The spotted sea bass ( Matte et al.  populations and revealed that this ratio increased linearly with increasing temperature. This could result in different trade‐offs related to mortality and growth in this species. In addition, it has been widely discussed in recent years that trade‐offs between growth and predator avoidance involving various physiological and behavioural traits such as swimming ability  than their low‐latitude conspecies  was recently discriminated from the Japanese sea bass (L. japonicus) as a newly recharacterized species with noticeable morphological and genetic differences  approach to detect genome‐wide SNP sites based on an assembled reference genome of 22.1We performed whole‐genome resequencing of 100 spotted sea bass collected from 14 sites (ten samples from each site in the Beibu Gulf and the Bohai Gulf and five samples from each other site) along the coastline of China Figure . White mL. maculatus and the genomes of related species    , gene diversity (Hs), and Fis statistics, were calculated using the R package “hierfstat” (version 0.5–7) Goudet, . The mea2.3FST values among populations were calculated within each chromosome using Plink2 (version v2.00a3)   and three temperature differences  were used to model the genetic differentiation. Dgcc was calculated from longitude and latitude coordinates using the following equations:R, φ1, φ2, and ∆λ are the Earth's radius (6371.393 km), the latitude of one site, the latitude of the other site, and the difference in longitude between the two sites, respectively. Dcsl was calculated based on the preprocessed OpenStreetMap data obtained from the Planet OSM website (https://osmdata.openstreetmap.de). Raw data in shapefile format were transformed into “Mercator” projection using the R package “sf” (version 0.9.7) and then divided into 0.1 × 0.1‐km2 grids. Finally, Dcsl was calculated as the sum length of the diagonal lines of all grids connecting two places. Daily SSTs from 1971 to 2010 were extracted from NOAA high‐resolution SST data (https://psl.noaa.gov/) . Their confidence intervals were generated after 5000 bootstraps by the “booteval.yhat” function.To model how a single factor influences the genetic distance, single‐factor linear regression between genetic distances and exogenous geographic and climatic variables was implemented using the “statsmodels” Python library (version 0.12.1) for IBD and IBE analyses. When attempting to dissect the effects of IBD and IBE patterns, the main challenge we faced was multicollinearity among exogenous variables. To address this, three mutually independent methods with high tolerances for multicollinearity were employed to solve the problem. Regularized least squares (RLS) regression is a family of relatively new linear regression techniques that were recently introduced for solving problems of confounding and causality plaguing genome‐environment association studies    and nucleotide diversity were estimated using VCFtools (version 0.1.15) . The extent of haplotype homozygosity (Rsb) was calculated for each SNP using the R package “rehh” (version 3.0.1) . In addition, Tajima's D index was estimated using VCF‐kit (version 0.1.6)   was used to identify genomic regions that have undergone positive selection in the northern (BH) and southern (BB) populations. The fixation index .Finally, Metascape (version 3.5)  gene on protein thermostability, the dominant alleles of each population and each nonsynonymous mutation were first applied to the reference myhz2 coding sequence to derive BH‐ and BB‐specific protein sequences. The tertiary structures assumed by proteins with these two sequences were then predicted using I‐TASSER (version 5.1)  remained for processing in the downstream steps. Of these, 783.6 billion clean reads were mapped to the reference genome of h Figure . We also3.2As shown in Figure We built an NJ tree by taking a related species  as the outgroup Figure . The roo3.3Dcsl and Dgcc had higher goodness of fit  and greater significance (p = 2.57E‐19 and 2.76E‐17) than those fitted using Dlat   and a p value (7.53E‐16) that was much lower than those associated with the other two factors, indicating a more significant correlation with genetic distance  Figure . In IBE e Figure .Dcsl and SSTmax simultaneously explained most of the variation in genetic distance and that SSTmax had a greater effect than did Dcsl on genetic distance. In LASSO regression, only Dcsl and SSTmax had nonzero coefficients   Table . All inds Figure . Althougx Figure .Dcsl and SSTmax showed very different patterns in PSR‐specific GDM. Genetic differentiation within PSRs was largely affected by SSTmax, whereas Dcsl had only a slight effect  with RDA to detect SNPs associated with SSTn Figure . The RDAs Figure . Function Figure . SSTmin‐s Figure . The enr3.5ω, Rsb, Tajima's D, and CSS, whereas higher FST suggested that the BH‐PSRs are more thoroughly differentiated  and “embryonic neurocranium morphogenesis” (GO: 0048702), contained a series of genes that are also probably instrumental in visual system development  and subsequent enrichment clustering to explore biological processes associated with climatic adaptation. As a result, we identified nine nonredundant enrichment clusters consisting of nine functional categories based on 34 BH‐PSGs Figure . The twot Figure .44.1L. maculatus lives in nearshore waters and has limited migration ability  that differ greatly in their genetic compositions Figure . MoreoveThe Chinese sea bass is one of China's most important aquaculture species, ranking second in annual production among aquaculture fishes  and IBE (Dcsl) analyses (VIF = 9.767), and this brings a challenge to the dissection and comparison of the effectiveness of these two patterns. We employed three mutually independent methods, LASSO, GDM, and CCA, to address this issue. The results obtained using these three approaches agree that neither the effects of Dcsl nor those of SSTmax can be ignored when modelling the genetic differentiation of spotted sea bass  of the five Igfbp genes  gene, an important negative regulator of the GH/IGF‐1 axis. The product of this gene can competitively bind to Igf‐1r and thereby impede the function of IGF‐1 in various species  and southern (BB) populations differ greatly. The most significantly enriched functional category of BH‐PSGs, “regulation of insulin‐like growth factor (IGF) receptor signalling pathway”, included four  than their southern conspecifics (1.7 g/d) (Chen et al., The divergent patterns of PSG enrichment found in the two populations suggest that the populations may adopt different strategies that involve different trade‐offs between growth and mortality. It has been demonstrated that a higher capacity for growth is a common adaptation to shorter growing seasons in high‐latitude environments (Angilletta et al., It is worth noting that dissection of the interactions of the genome of an organism with the environment is very complicated. The presence of relatively sparse sampling sites and multicollinearity among geographic and environmental factors undoubtedly increase the challenge. Therefore, the findings of this study should be validated by quantitative studies of adaptive traits followed by common garden‐variety experiments in the future.The authors declare that they have no conflict of interest. The authors alone are responsible for the content and writing of the article.Appendix S1Click here for additional data file.Table S1Click here for additional data file.Figure S1Click here for additional data file.