Well‐being spectrum traits are associated with polygenic scores for autism

Individuals with autism spectrum disorder (ASD) tend to experience lower well‐being as demonstrated mostly for children and adolescents in epidemiological studies. A further investigation of inclusive well‐being, in terms of five well‐being spectrum (5‐WBS) traits including neuroticism, depression, loneliness, life satisfaction, and positive affect, among adults with ASD may deepen our understanding of their well‐being, and lead to the possibility to further modify societal supportive mechanisms for individuals with ASD. This study aims to investigate if a genetic predisposition for ASD is associated with 5‐WBS traits using polygenic risk score (PRS) analysis. PRS for ASD were calculated based on the latest genome‐wide association study of ASD by the Psychiatric Genetics Consortium (18,381 cases, 27,969 controls) and were created in the independent cohort UK Biobank. Regression analyses were performed to investigate the association between ASD PRS and 5‐WBS traits in the UK Biobank population including 337,423 individuals. ASD PRS were significantly associated with all 5‐WBS traits, showing a positive association with the negative WBS traits, neuroticism (max R2 = 0.04%, p < 1 × 10−4), depression (max R2 = 0.06%, p < 1 × 10−4), loneliness (max R2 = 0.04%, p < 1 × 10−4), and a negative association with the positive WBS traits, life satisfaction (max R2 = 0.08%, p < 1 × 10−4), positive affect (max R2 = 0.10%, p < 1 × 10−4). The findings suggest that adults carrying a high load of risk single nucleotide peptides (SNPs) for ASD are more likely to report decreased well‐being. The study demonstrates a considerable connection between susceptibility to ASD, its underlying genetic etiology and well‐being.

While ASD is highly heritable, the genetic context of the well-being of individuals with ASD is still unknown.Based on available knowledge of genome-wide detected genetic variants associated with ASD, we constructed polygenic risk scores for ASD and explored to what extent the additive genetic risk for ASD is associated with well-being based on a large population-based dataset from the United Kingdom.We demonstrate that individuals, who are genetically predisposed to ASD are prone to experience poor well-being, as reflected by higher negative and lower positive well-being trait scores compared with individuals with a low genetic risk load for ASD.The findings of this study highlight well-being as an important health-related factor, which appears to be considerably linked to genetic susceptibility for ASD.

INTRODUCTION
Autism spectrum disorder (ASD) comprises a group of complex neurodevelopmental disorders with lifelong persistence, and is characterized by difficulties in social communication, restricted interests, and repetitive behaviors (American Psychiatric Association, 2000).It is estimated that 1%-2% of individuals are affected by ASD (Grove et al., 2019;NHS Digital, 2018) worldwide.Several previous studies have suggested that individuals with ASD suffer from poor mental well-being (Stimpson et al., 2021) and lower quality of life (Ayres et al., 2018;de Vries & Geurts, 2015;Moss et al., 2017).It has been observed that ASD is associated with neuroticism (Austin, 2005;Schriber et al., 2014;Schwartzman et al., 2016;Wakabayashi et al., 2006) and mental health conditions such as depression (Hudson et al., 2019).Individuals with ASD often exhibit more loneliness (Lasgaard et al., 2010;Sundberg, 2018;Suzuki et al., 2021;Whitehouse et al., 2009) and social anxiety (Stimpson et al., 2021), as well as lower degrees of happiness (McChesney & Toseeb, 2018;Scheeren et al., 2021) and life satisfaction (Franke et al., 2019).While well-being is known to be imperative for emotional, cognitive, and interpersonal benefits, good health, and longevity of life, a comprehensive understanding of the link between the traits belonging to the well-being spectrum (WBS) and ASD is still lacking.Prior ASD studies have mostly focused on children and adolescents (Mukaetova-Ladinska et al., 2012) and explored the associations between ASD and different aspects of mental and social well-being in an epidemiological context.Further exploration of the link between ASD and well-being in a genetic context may contribute to a deeper understanding of the relationship between ASD and well-being.
Interestingly, there is hardly any genetic study that has investigated well-being comprehensively in relation to ASD.Grove et al. (2019) reported the most recent ASD related GWAS and additionally explored the extent of genetic overlap between ASD and 234 different phenotypes belonging to psychiatric diseases, disorders, and traits.Depression was found to have a significant genetic overlap with ASD, while neuroticism and subjective wellbeing, measured by the question "How do you feel?" presented moderately significant genetic overlap (Okbay et al., 2016).These findings further indicate and highlight the importance of investigating these three WBS traits among ASD individuals in an extended genetic context to be able to understand the nature of association in both a qualitative and quantitative manner.No prior reports are available regarding the association between a genetic predisposition for ASD and loneliness, positive affect, or happiness.
While previous studies have considerably advanced our understanding of the association between ASD and traits belonging to 5-WBS, these studies were primarily of epidemiological nature, focused on specific WBS traits separately, included only small cohorts, limited in clinical samples, and most often children or adolescents (Austin, 2005;Franke et al., 2019;Hudson et al., 2019;Lasgaard et al., 2010;McChesney & Toseeb, 2018;Scheeren et al., 2021;Schriber et al., 2014;Schwartzman et al., 2016;Sundberg, 2018;Suzuki et al., 2021;Wakabayashi et al., 2006;Whitehouse et al., 2009).There is a considerable gap in studies investigating well-being of adults with ASD, even though adulthood is the most stable period of age for such investigations (Costa & McCrae, 1988).Furthermore, a comprehensive exploration of the 5-WBS traits in connection to the genetic predisposition of ASD and, thus, in an etiological context is currently missing.
In this study, we aimed to use a powerful polygenic approach, based on PRS derived from the most recent available GWAS for ASD, to investigate the etiological association between ASD susceptibility and WBS traits in a large European adult population.Specifically, we explored the genetic propensity for ASD in association with the 5-WBS; which comprises (1) negative well-being traits including neuroticism, depression, and loneliness, and (2) positive well-being traits, including life satisfaction and positive affect.The study is based on the comprehensive UK Biobank, which contains a large spectrum of phenotypic and high-quality genetic data retrieved from more than 500,000 individuals.

Participants
We used baseline data from the UK Biobank (UKB) project, one of the largest prospective European populationbased cohorts.Participants aged 40-69 years were recruited between 2006 and 2010.A detailed description has been published elsewhere (Bycroft et al., 2018).At baseline assessment, participants provided physical measures and biological samples in addition to taking part in computer-assisted self-administered questionnaires and face-to-face interview (Sudlow et al., 2015).We restricted our analysis to participants of European ancestries (Bycroft et al., 2018) based on self-report and multidimensional scaling (UKB data field 22006), which fits to the data of the ASD GWAS that has been conducted on participants of European ancestry (Martin et al., 2019).We excluded participants who had withdrawn consent (N = 203), had non-Caucasian origin (N = 92,859), were not qualified for standard quality control (QC; Marees et al., 2018;N = 72,131), showed a sex mismatch between reported and genetic data (sex has been used as a covariate in the study and with this restriction we were able to covary correctly) or were outliers regarding heterozygosity and genetic relatedness (detailed below).Finally, 337,423 (N) participants (46% male) were considered for the study model (Fowchart 1A) and the main analysis (PRS and association analyses).Within the UK Biobank cohort, we identified 210 self-reported ASD cases (0.1%) using data field 20544 ("Mental Health problems ever diagnosed by a professional"; Flowchart 1B).However, this 0.1% prevalence is lower than the reported prevalence for ASD in the UK (1%-2%; Grove et al., 2019;NHS Digital, 2018).Given the small number of self-reported individuals with ASD diagnosis in the UK Biobank, only the phenotypic information status of these ASD cases is briefly explored.No further statistical analysis has been performed for this group.

Phenotypic information
The phenotypes of interest in the study were the traits belonging to the 5-WBS traits (Histograms in Figure S1).Three phenotypes belonged to the negative end of the WBS, that is, "neuroticism," "depression," and "loneliness."Two phenotypes belonged to the positive end of the WBS spectrum, that is, "life satisfaction" and "positive affect."UKB baseline data were used for the retrieval of the phenotypic information and the association analyses.Individuals were excluded when belonging to the group of "Participants with missing data," or when answering "prefer not to answer" or "Do not know."In the case of UKB Data-field 4537 (work/job satisfaction), participants responding "I am not employed" were excluded from further analysis regarding "Life satisfaction," as satisfaction related to work/job was considered to be only evaluated adequately by individuals who were working or employed at the time point the question was posed.The neuroticism score (UKB Datafield 20127) was measured on the included participants' (N = 274,266) response to 12 questions from the Eysenck Personality Inventory Neuroticism -Revised (EPIN-R) scale (Eysenck & E. S., 1975).The score ranges from 0 to 12, with higher scores representing a higher level of neuroticism.Information on depression was collected from included participants' (N = 335,328) response to the UKB touchscreen question "Have you ever seen a general practitioner (GP) for nerves, anxiety, tension or depression?" (UKB Data-field 2090).Loneliness of included participants (N = 332,479) was assessed via the UKB touchscreen question "Do you often feel lonely?" (UKB Data-field 2020).Both "depression" and "loneliness" were available as dichotomous (Yes/No) variables.Information on life satisfaction of included participants (N = 74,607) was extracted from 5 touchscreen-based questions: (1) "In general how satisfied are you with your family relationships?" (UKB data-field 4559), ( 2) "In general how satisfied are you with your financial situation?"(UKB data-field 4581), (3) "In general how satisfied are you with your friendship?" (UKB data-field 4570), ( 4) "In general how satisfied are you with your work?" (UKB data-field 4537), and ( 5) "In general how satisfied are you with your health?" (UKB data-field 4548).Responses were re-coded on a six-point scale (extremely happy = 6, very happy = 5, moderately happy = 4, moderately unhappy = 3, very unhappy = 2, and extremely unhappy = 1).Surveying across these five components of life for the model domain of life satisfaction has been previously suggested (Diener et al., 1999).Measuring these phenotypic data on the same six-point assessment scale for "life satisfaction" has been reported to be effective (Weiss et al., 2016).Following a similar approach as reported by Weiss et al. (2016), an average score was calculated for the individual life satisfaction, taking into account all five variables available in UKB, that covered information on individual life-related satisfaction.A higher score corresponded to a higher level of life satisfaction.Information on positive affect of included participants (N = 111,024) was collected based on the UKB touchscreen question "In general how happy are you?"(UKB Data-field 4526).We recoded the variable ranging from 1 to 6 with a higher score representing a higher value.

Genotype QC
We used imputed genotyping data from the UKB in this study (Bycroft et al., 2018).Our QC procedure followed recommendations for PRS construction using UKB data and QC steps (Bycroft et al., 2018;Collister et al., 2022).Analyses were restricted to SNPs with a MAF > 0.5, with an imputation information score (INFO) > 0.8, and genotype missingness <0.02.The imputation program IMPUTE2 (Howie et al., 2011) has been used for genetic data imputation in UKB, which reports INFO values between 0 and 1, where a value near 1 represents a higher certainty of the SNP's imputation (Zheng et al., 2015).
We included only participants with QC led genetic data available in UKB (data-field 22020) to be able to exclude individuals with a missing rate >0.02 on autosomes, with sex discordance, who were outliers for heterozygosity, who were genetically related (up to thirddegree relatives) or of "non-White British" ethnicity based on genetic grouping (UKB data-field 22006).

PRS analyses and regression analysis
PRS computation was done for each UKB participant using the clumping and thresholding algorithms in PRSice-2 (Choi & O'Reilly, 2019;Euesden et al., 2015).In brief, the algorithm computes a polygenic score in a target sample by calculating the sum of all traitassociated alleles, weighted by the effect size of each allele in an independent sample generated from a base GWAS.The latest iPSYCH-PGC ASD GWAS summary statistics (released in November 2017; Grove et al., 2019) was used as the base dataset.This dataset was based on 18,381 individuals with autism and 27,969 individuals from the general population (Grove et al., 2019).The PRS calculated from the GWAS explained a variance of 2.45% when using a unique Danish population based on five different sets of target and training samples.The SNP-based heritability (h 2 SNP ) was calculated as 0.118.SNPs in linkage disequilibrium (LD) were grouped.We clumped SNPs using an LD-based r 2 ≥ 0.1 and a 250 kb genomic distance.PRS were calculated following the high-resolution scoring (Euesden et al., 2015) method to produce "best-fit PRS," that were identified as most predictive for each phenotype, that is, explaining a maximum variance (R 2 ) of the phenotype across the considered range of GWAS association p-value thresholds (pT).A range of pT = 0.0001 to pT = 0.5 at increments of 0.00005 was covered.Nagelkerke's pseudo R 2 were used to measure the explained variance of the binary phenotypes.Logistic and linear regression analyses were conducted to determine associations between ASD PRS and phenotypes.Age, sex, genotyping batch, and the first 20 genetic principal components were included as covariates in the model."Empirical p-values" were obtained by performing permutations k times with a value of 10,000.
Here, the target trait values were permuted across the individual values k times.The resulting empirical p-value was used to assess the significance for each analysis to control for Type-1 error and overfitting (Choi et al., 2020;Choi & O'Reilly, 2019).The area under the receiver operating characteristic curves (AUC) of the ASD PRS for each phenotype was calculated to evaluate the predictive accuracy of the PRS model (Collister et al., 2022;Dudbridge, 2013;Lee et al., 2012).PRSice 2.3.5 and R (version 3.6.3)were used for statistical analysis.

RESULTS
Individuals with ASD in the UK biobank show increased rates for negative and lower rates for positive WBS traits Prior to the main PRS construction and association analysis investigating the link between ASD PRS and 5-WBS traits, we first explored the individuals with self-reported diagnosed ASD in UKB in relation to the primary phenotypes of this study.We observed that individuals with ASD (N = 210; Section 2) have increased mean scores for negative WBS traits and lower mean scores for positive WBS traits (Table S1).Regression analyses investigating the association between WBS traits and ASD revealed positive associations with the negative WBS traits neuroticism (β 2.9, 95% CI 2.4-3.3,p < 1 Â 10 À4 ), depression (OR 5.9, 95% CI 4.3-7.9,p < 1 Â 10 À4 ), and loneliness (OR 4.45, 95% CI 3.4-5.9,p < 1 Â 10 À4 ) and negative associations with the positive WBS traits life satisfaction (β À 0.6, 95% CI À0.8 to À0.4, p < 1 Â 10 À4 ) and positive affect (β À 0.7, 95% CI À0.9 to À0.5, p < 1 Â 10 À4 ; Table S1).Analyses were corrected for the effects of age and sex.

ASD PRS are associated with both positive WBS traits
PRS for ASD significantly predicted both positive WBS traits, life satisfaction (853 SNPs, R 2 = 0.08%, pT = 0.0009, p < 1 Â 10 À4 , AUC 0.56), and positive affect (50,192 SNPs, R 2 = 0.10%, pT = 0.2924, p < 1 Â 10 À4 , AUC 0.53) as illustrated in Figure 1.Significant predictions were obtained at all thresholds as depicted in Figure S2.Details of the high-resolution bestfit PRS analyses of ASD for the positive WBS traits can be found in Table S2.Quantile plots for life satisfaction and positive affect show the inverse associations between ASD PRS and both positive WBS traits (Figure 2), demonstrating a stepwise decrease of these traits with increasing PRS loads.

DISCUSSION
This study is the first to investigate the genetic propensity of ASD to associate with all the 5-WBS traits.We show that individuals with a higher genetic predisposition for ASD are more likely to experience poor well-being in life irrespective of age and sex.Using PRS derived from the recently published largest GWAS for ASD, we detected that a higher polygenic risk for ASD is positively associated with the negative WBS traits "neuroticism," "depression," "loneliness," and inversely associated with the positive WBS traits "life satisfaction," "positive affect."Notably, this paper is the first that describes the evidence of associations between ASD-linked SNPs and the well-being traits "loneliness" and "positive affect," giving further insight into the role of ASD-related genetics for well-being.
Our investigation on WBS demonstrates that individuals who are genetically predisposed to ASD show a significant and overall reduced level of well-being.Previous epidemiological reports that investigated the 5-WBS traits in association with ASD, reported that individuals with ASD tend to show a neurotic personality (Austin, 2005;Schriber et al., 2014;Schwartzman et al., 2016;Wakabayashi et al., 2006), are more inclined to be depressed (Hudson et al., 2019), have a higher likelihood to suffer from loneliness (Lasgaard et al., 2010;Sundberg, 2018;Suzuki et al., 2021;Whitehouse et al., 2009), and to experience lower life satisfaction (Franke et al., 2019) and lower positive affect in life F I G U R E 1 Associations between polygenic risk scores for autism spectrum disorder and the five well-being spectrum traits neuroticism, depression, loneliness, life satisfaction, and positive affect.Values displayed next to each bar represent the p-value for significance for the most predictive (best-fit) models.The "empirical p-value" significance threshold for all traits was set at 1 Â 10 À4 as found for every trait.Given that depression and loneliness were binary traits, the variance explained for these traits were measured using Nagelkerke's pseudo R 2 .
F I G U R E 2 Quantile plots for autism spectrum disorder polygenic risk score (PRS) show the nature of the associations between PRS load and well-being spectrum trait outcome.Increasing polygenic risk scores lead to an increase in the traits "neuroticism," "depression," and "loneliness," and to a decrease in the traits "life satisfaction" and "positive affect."Regression analyses were performed with traits as an outcome and each 5% quantile separately, where the PRS sample distribution was divided into 20 equally sized quantiles.Each quantile effect size was compared with the central quantile (reference point).Each regression included the covariates used in the main analysis.(McChesney & Toseeb, 2018;Scheeren et al., 2021).However, besides one meta-analysis investigating the association between depression in ASD (Hudson et al., 2019), all these epidemiological studies were hitherto characterized by sample size limitation, were questionnaire-based and included mostly adolescents or clinical samples.Important examples include the observation that higher neuroticism is associates with autistic traits as shown in (N = 37-828) clinical (Schriber et al., 2014;Schwartzman et al., 2016) and in (N = 201-320) population-based (Austin, 2005;Wakabayashi et al., 2006) studies.Furthermore, it has been shown that loneliness appears more often among adolescents with ASD (N = 35-85; Lasgaard et al., 2010;Sundberg, 2018;Suzuki et al., 2021;Whitehouse et al., 2009) as well as poor life satisfaction (N = 46; Franke et al., 2019).A recent systematic review on Quality of Life (Ayres et al., 2018) and small-scale epidemiological studies (N = 52-120; de Vries & Geurts, 2015;Moss et al., 2017) reported similar observations.Positive affect or happiness (used as interchangeable terms in different studies) was observed to be lower among individuals with ASD compared to individuals without ASD in clinical samples of children (N = 408;McChesney & Toseeb, 2018) or in adults (N = 917; Scheeren et al., 2021).We explore these findings further by studying the genetic propensity for ASD using PRS in about 350,000 adults in a nonclinical cohort, strengthening the epidemiological observations by high statistical power and allowing to draw conclusions for a general adult population.It is important to highlight that our study presents results for all traits belonging to the 5-WBS based on the very same cohort, while earlier studies often focused on WBS traits separately.
We demonstrate that individuals with many risk alleles for ASD are more likely to show feelings of loneliness and a lower positive affect in life than those with fewer risk alleles.To the best of our knowledge, these are the first reports of genetic association of ASD with these traits based on genome-wide data.While ASD is known to be highly heritable (Colvert et al., 2015), loneliness (Abdellaoui et al., 2018) and positive affect (Bartels, 2015) have been reported to be of modest heritability.Therefore, it can be hypothesized that a genetic overlap of loneliness and positive affect with ASD may be abundant based on evidence of genetic predisposition association.However, to further strengthen, the understanding, additional research is required to explore the genetic pathways and neurobiological mechanisms behind such associations.
Investigating the other three WBS traits neuroticism, depression, and life satisfaction, we demonstrate that a higher polygenic load for ASD is significantly associated with higher rates of neuroticism, higher rates of depression, and lower rates of life satisfaction.We observe that the nature of the association is consistent with increasing polygenic load.Our analyses expand recent observations of the genetic overlap between ASD and these traits (Grove et al., 2019).Furthermore, our study explored life satisfaction as an overall composite of the five domains of life, family relationship, financial situation satisfaction, friendship, work/job, and health (Diener et al., 1999).Thus, the analyses deliver robust results concerning the connection between subjective well-being (Okbay et al., 2016) and ASD, taking the heterogeneity of "subjective well-being" into consideration compared with earlier studies exploring with only a limited number of questions (Okbay et al., 2016).
We show that the ASD PRS significantly predicted explained variance of WBS traits, where the variances explained were ≤0.10%.While these proportions may seem to be quite small, the magnitude is not unexpected to be found in a general population, as we investigate in our study.The observed percentages are roughly in line with previous studies investigating ASD PRS in association with other traits.Earlier studies observed rates of <0.5% for "cognitive aptitude" (Clarke et al., 2016), 0.10%, 0.11%, and 0.13% for "childhood trauma," "selfharm ideation," and "self-harm," respectively (Warrier & Baron-Cohen, 2021); 0.17% for "childhood behavior," 0.24% for "rigidity," and 0.54% for "attention to detail" (Bralten et al., 2018) and 0.41% for "everyday executive function" (Torske et al., 2020).Our presented quantile analysis further demonstrates the nature of the associations between PRS for ASD and traits of interest, and highlights the potential to stratify individuals at risk for ASD for their risk to show a decreased well-being based on their ASD-associated PRS (Krapohl et al., 2016).These observations highlight the robustness and strength of the findings.While our PRS is based on the latest available largest ASD GWAS, the percentage of "explaining variance" may be further increased by an even larger sample size of the discovery dataset and enrichment of significant markers included in the GWAS (Dudbridge, 2013).We found the predictive accuracy of the ASD PRS to be in the range between 0.51 and 0.56 for the investigated 5-WBS traits, which is borderline accurate to establish prediction, considering 0.50 as the cutoff point for lack of discrimination (Hanley & McNeil, 1982).However, the accuracy may further increase in power with a modest increase in the sample size of subjects in the discovery dataset or GWAS summary dataset (Dudbridge, 2013).In light of these aspects, the findings made in our study can be considered robust.
While we show that individuals genetically predisposed to ASD are inclined to experience poor well-being in life, the results need to be interpreted with caution taken into account the gene-environment interactions.Well-being largely depends on environmental factors, and genes instead of directly shaping well-being experiences, contribute to brain development and the processing of information acquired from the environment.Taking this into account, we hypothesize a few mechanisms by which genetic predisposition for ASD may be associated with well-being.First, elevated PRS for ASD could result in communication, social relationship, and behavior problems (Bralten et al., 2018;St Pourcain et al., 2018), which possibly in turn result in difficulties to cope at everyday places of life such as at home, at workplace, and at friends' or relatives' places.This may lead to increased social distance or exclusion, and subsequently increase feelings of loneliness and lower life satisfaction (Diener et al., 1999).Second, often receiving negative attitude from others since an early age (Humphrey & Hebron, 2015;Maïano et al., 2016), failing to achieve and being compared with others at different stages of life (Biklen, 2020;Williams et al., 2019) since birth may contribute to developing a neurotic personality and lower positive affect in life.Third, the lack of understanding of the own state of health, the late or absence of diagnosis of ASD (Huang et al., 2020; leading to lack of social support), as well as the difficulties with the workplace (Chan et al., 2018) and surrounding environments may explain the higher risk for depression among individuals with ASD.Therefore, modification of environmental factors may alter the outcome considerably.For instance, early diagnosis and ensuring a supportive environment for the individuals genetically predisposed to ASD may improve their well-being throughout the adulthood.However, future research focusing on environmental and behavioral factors may need to explore these hypothesized aspects further.Moreover, well-being has been of interest in different research fields like sociology, economics, and psychology regarding the concept of subjective and objective well-being (Ryan & Deci, 2001;Voukelatou et al., 2021).And, this is always a matter of context of how the well-being construct is reflecting the actual individual situation.For decades subjective wellbeing has been the top choice for researchers as the primary index of well-being (Ryan & Deci, 2001).Moreover, recent studies suggest that individuals with ASD tend to respond well when subjective well-being measures were used for the analysis of well-being (Bishop-Fitzpatrick et al., 2016;Bishop-Fitzpatrick et al., 2017).For this study, well-being measures considered mostly subjective responses that were answered by the UKB participants.However, objective measures for well-being, which were not in the scope of our study, such as academic success or living conditions may add some further information to the topic.Furthermore, differences in the perception of well-being or quality of life among individuals with ASD compared with others without ASD are discussed for a long time (Lam et al., 2021;Pellicano et al., 2022).From that point of view, our study results need to be interpreted with caution.Moreover, this study addressed the general population with a large number of participants of middle to older adult age (>40 years), who may have different perception of well-being than young adults especially emerging adulthood (e.g., 18-25 years; Cribb et al., 2019;Sosnowy et al., 2018).Thus, the study investigates and reflects especially the interaction of ASD-linked genetics and well-being in the middle aged and older adult population.Future studies which may include tailored study plans and questionnaires for individuals with ASD (Øverland et al., 2022), may further and in-depth study the gene-well-being interaction specifically in ASD.
Strengths of this study include the use of the powerful PRS tool that utilizes the latest largest ASD GWAS (iPSYCH-PGC) and one of the largest cohorts with quality genetic data (UKB), which allowed performing this study with high statistical power and a reliable assessment of 5-WBS.Our application of both, the "highresolution best-fit" PRS and the "empirical p-value" combined approach in PRS analysis is first to report and have been suggested to have higher predictive accuracy than similar methods (Choi & O'Reilly, 2019;Euesden et al., 2015).While large population-based cohorts often have underreported ASD cases (Warrier & Baron-Cohen, 2021), but are enriched with high-quality genetic data, detailed living-related outcomes, and demographic data, the application of PRS method allowed the exploration of genetic data linked to the underreported diagnosis and assessing direct association with large populationbased well-being data.
There are a number of limitations in this study to be mentioned.First, the UKB cohort is known to have a healthy volunteer bias (Fry et al., 2017) and we also observed lower ASD prevalence (0.1%) compared with the prevalence of ASD in the UK (1%-2%; Grove et al., 2019;NHS Digital, 2018); suggesting that the observed association of WBS traits with ASD may differ in the general population.However, the report (Fry et al., 2017) compares especially the demographic characteristics in UKB, while our study addresses the genetic propensity, which is fixed at birth and the reverse associations to be confounded by other factors are less likely.Second, while the PRS for ASD were constructed using the most recent and largest GWAS to date for ASD, the ASD PRS still explains only a lower total variance of 2.5% compared with h 2 SNP of 11% for ASD, which has been earlier described (Grove et al., 2019).However, advancements in future GWAS with larger sample sizes and the application of advanced PRS methods as presented here may potentiate the understanding of the etiological associations observed in this study.Third, rare variants and CNVs collectively explain <5% of the overall liability in ASD (De Rubeis et al., 2014;Gaugler et al., 2014;Iossifov et al., 2014).This study focused only on common variants, known to account for the major part of ASD liability (Gaugler et al., 2014;Warrier & Baron-Cohen, 2021).Future studies may also consider rare variants and CNVs for the construction of ASD PRS to further precise the genetic instrument for genetic association studies.Fourth, this study as a study of adults with ASD, only reflects the response of the middle to elderly aged (40-69 years) adult participants.A certain section of adults such as young adults (above adolescence-40 years) are not considered, as the study was based on the UKB population.Future studies may explore and compare these findings among young adults in other cohorts covering a broad range of adult age.Finally, our study cannot robustly infer causality, due to the fact that PRS predictions are only able to investigate a causal status in one direction (Plomin & von Stumm, 2022).Therefore, our investigation strengthens and potentiates the epidemiological understanding of simple associations into correlations (Altman & Krzywinski, 2015) between ASD and WBS, while acting as a potential step toward identifying causality (Pingault et al., 2018).
The current study shows that a genetic predisposition for ASD assessed with standard PRS is significantly associated with poor well-being.The findings give new potential insights into etiological mechanisms underlying the connection between ASD and poor well-being.Extending our findings in future studies with direct assessments of ASD traits using questionnaires or screening tools such as the Autism Spectrum Quotient is recommended.Future advancement and empowerment of ASD GWAS with additional significant loci and a higher number of cases may enable the performance of Mendelian Randomization analysis for firmer causality assessments.Our study results support the importance of further optimization of the policies regarding supportive care for an improvement of the well-being of individuals with ASD.

AUTHOR CONTRIBUTIONS
Salahuddin Mohammad wrote the article with support from Markus J. T. de Ruijter, Gull Rukh, Mathias Rask-Andersen, Helgi B. Schiöth, and Jessica Mwinyi.Salahuddin Mohammad designed the work and performed the analysis.Markus J. T. de Ruijter contributed to the analysis.Markus J. T. de Ruijter, Gull Rukh, Mathias Rask-Andersen, Helgi B. Schiöth, and Jessica Mwinyi provided critical revision of the article.All authors have read and agreed to the published version of the article.