Phenome-wide screening of the putative causal determinants of depression using genetic data.

Depression is one of the most common mental health disorders and one of the top causes of disability throughout the world. The present study sought to identify putative causal associations between depression and hundreds of complex human traits through a genome-wide screening of genetic data and a hypothesis-free approach. We leveraged genome-wide association studies summary statistics for depression and 1504 complex traits and investigated potential causal relationships using the latent causal variable method. We identified 559 traits genetically correlated with depression risk at FDR < 5%. Of these, 46 were putative causal genetic determinants of depression, including lifestyle factors, diseases of the nervous system, respiratory disorders, diseases of the musculoskeletal system, traits related to the health of the gastrointestinal system, obesity, vitamin D levels and the use of prescription medications, among others. No phenotypes were identified as potential outcomes of depression. Our results suggest that genetic liability to multiple complex traits may contribute to a higher risk for depression. In particular, we show a putative causal genetic effect of pain, obesity and inflammation on depression. These findings provide novel insights into the potential causal determinants of depression and should be interpreted as testable hypotheses for future studies to confirm, which may facilitate the design of new prevention strategies to reduce depression's burden.

Genetic overlap between cortical brain morphometry and frontotemporal dementia risk.

Frontotemporal dementia (FTD) has a complex genetic etiology, where the precise mechanisms underlying the selective vulnerability of brain regions remain unknown. We leveraged summary-based data from genome-wide association studies (GWAS) and performed LD score regression to estimate pairwise genetic correlations between FTD risk and cortical brain imaging. Then, we isolated specific genomic loci with a shared etiology between FTD and brain structure. We also performed functional annotation, summary-data-based Mendelian randomization for eQTL using human peripheral blood and brain tissue data, and evaluated the gene expression in mice targeted brain regions to better understand the dynamics of the FTD candidate genes. Pairwise genetic correlation estimates between FTD and brain morphology measures were high but not statistically significant. We identified 5 brain regions with a strong genetic correlation (rg > 0.45) with FTD risk. Functional annotation identified 8 protein-coding genes. Building upon these findings, we show in a mouse model of FTD that cortical N-ethylmaleimide sensitive factor (NSF) expression decreases with age. Our results highlight the molecular and genetic overlap between brain morphology and higher risk for FTD, specifically for the right inferior parietal surface area and right medial orbitofrontal cortical thickness. In addition, our findings implicate NSF gene expression in the etiology of FTD.

Phenotypic and genetic factors associated with donation of DNA and consent to record linkage for prescription history in the Australian Genetics of Depression Study.

Samples can be prone to ascertainment and attrition biases. The Australian Genetics of Depression Study is a large publicly recruited cohort (n = 20,689) established to increase the understanding of depression and antidepressant treatment response. This study investigates differences between participants who donated a saliva sample or agreed to linkage of their records compared to those who did not. We observed that older, male participants with higher education were more likely to donate a saliva sample. Self-reported bipolar disorder, ADHD, panic disorder, PTSD, substance use disorder, and social anxiety disorder were associated with lower odds of donating a saliva sample, whereas anorexia was associated with higher odds of donation. Male and younger participants showed higher odds of agreeing to record linkage. Participants with higher neuroticism scores and those with a history of bipolar disorder were also more likely to agree to record linkage whereas participants with a diagnosis of anorexia were less likely to agree. Increased likelihood of consent was associated with increased genetic susceptibility to anorexia and reduced genetic risk for depression, and schizophrenia. Overall, our results show moderate differences among these subsamples. Most current epidemiological studies do not search for attrition biases at the genetic level. The possibility to do so is a strength of samples such as the AGDS. Our results suggest that analyses can be made more robust by identifying attrition biases both on the phenotypic and genetic level, and either contextualising them as a potential limitation or performing sensitivity analyses adjusting for them.

Shared Genetic Etiology between Cortical Brain Morphology and Tobacco, Alcohol, and Cannabis Use.

Genome-wide association studies (GWAS) have identified genetic variants associated with brain morphology and substance use behaviors (SUB). However, the genetic overlap between brain structure and SUB has not been well characterized. We leveraged GWAS summary data of 71 brain imaging measures and alcohol, tobacco, and cannabis use to investigate their genetic overlap using linkage disequilibrium score regression. We used genomic structural equation modeling to model a "common SUB genetic factor" and investigated its genetic overlap with brain structure. Furthermore, we estimated SUB polygenic risk scores (PRS) and examined whether they predicted brain imaging traits using the Adolescent Behavior and Cognitive Development (ABCD) study. We identified 8 significant negative genetic correlations, including between (1) alcoholic drinks per week and average cortical thickness, and (2) intracranial volume with age of smoking initiation. We observed 5 positive genetic correlations, including those between (1) insula surface area and lifetime cannabis use, and (2) the common SUB genetic factor and pericalcarine surface area. SUB PRS were associated with brain structure variation in ABCD. Our findings highlight a shared genetic etiology between cortical brain morphology and SUB and suggest that genetic variants associated with SUB may be causally related to brain structure differences.

The Effect of Genetic Predisposition to Alzheimer's Disease and Related Traits on Recruitment Bias in a Study of Cognitive Aging.

The recruitment of participants for research studies may be subject to bias. The Prospective Imaging Study of Ageing (PISA) aims to characterize the phenotype and natural history of healthy adult Australians at high future risk of Alzheimer's disease (AD). Participants approached to take part in PISA were selected from existing cohort studies with available genomewide genetic data for both successfully and unsuccessfully recruited participants, allowing us to investigate the genetic contribution to voluntary recruitment, including the genetic predisposition to AD. We use a polygenic risk score (PRS) approach to test to what extent the genetic risk for AD, and related risk factors predict participation in PISA. We did not identify a significant association of genetic risk for AD with study participation, but we did identify significant associations with PRS for key causal risk factors for AD, IQ, household income and years of education. We also found that older and female participants were more likely to take part in the study. Our findings highlight the importance of considering bias in key risk factors for AD in the recruitment of individuals for cohort studies.

Genomics-driven screening for causal determinants of suicide attempt.

OBJECTIVE: Each year, around one million people die by suicide. Despite its recognition as a public health concern, large-scale research on causal determinants of suicide attempt risk is scarce. Here, we leverage results from a recent genome-wide association study (GWAS) of suicide attempt to perform a data-driven screening of traits causally associated with suicide attempt. METHODS: We performed a hypothesis-generating phenome-wide screening of causal relationships between suicide attempt risk and 1520 traits, which have been systematically aggregated on the Complex-Traits Genomics Virtual Lab platform. We employed the latent causal variable (LCV) method, which uses results from GWAS to assess whether a causal relationship can explain a genetic correlation between two traits. If a trait causally influences another one, the genetic variants that increase risk for the causal trait will also increase the risk for the outcome inducing a genetic correlation. Nonetheless, a genetic correlation can also be observed when traits share common pathways. The LCV method can assess whether the pattern of genetic effects for two genetically correlated traits support a causal association rather than a shared aetiology. RESULTS: Our approach identified 62 traits that increased risk for suicide attempt. Risk factors identified can be broadly classified into (1) physical health disorders, including oesophagitis, fibromyalgia, hernia and cancer; (2) mental health-related traits, such as depression, substance use disorders and anxiety; and (3) lifestyle traits including being involved in combat or exposure to a war zone, and specific job categories such as being a truck driver or machine operator. CONCLUSIONS: Suicide attempt risk is likely explained by a combination of behavioural phenotypes and risk for both physical and psychiatric disorders. Our results also suggest that substance use behaviours and pain-related conditions are associated with an increased suicide attempt risk, elucidating important causal mechanisms that underpin this significant public health problem.

Discontinuation of antidepressant treatment: a retrospective cohort study on more than 20,000 participants.

BACKGROUND: Factors influencing antidepressant treatment discontinuation are poorly understood. In the present study, we aimed to estimate the prevalence of antidepressant treatment discontinuation and identify demographic characteristics, psychiatric comorbidities, and specific side effects associated with treatment discontinuation. METHODS: We leveraged data from the Australian Genetics of Depression Study (AGDS; N = 20,941) to perform a retrospective cohort study on antidepressant treatment discontinuation. Participants were eligible if they were over 18 years of age, had taken antidepressants in the past 4 years, and provided informed consent. RESULTS: Among the ten antidepressants studied, the highest discontinuation rates were observed for Mirtazapine (57.3%) and Amitriptyline (51.6%). Discontinuation rates were comparable across sexes except for Mirtazapine, for which women were more likely to discontinue. The two most common side effects, reduced sexual function and weight gain, were not associated with increased odds of treatment discontinuation. Anxiety, agitation, suicidal thoughts, vomiting, and rashes were associated with higher odds for treatment discontinuation, as were lifetime diagnoses of PTSD, ADHD, and a higher neuroticism score. Educational attainment showed a negative (protective) association with discontinuation across medications. CONCLUSIONS: Our study suggests that not all side effects contribute equally to discontinuation. Common side effects such as reduced sexual function and weight gain may not necessarily increase the risk of treatment discontinuation. Side effects linked to discontinuation can be divided into two groups, psychopathology related and allergy/intolerance.

Phenome-wide screening of GWAS data reveals the complex causal architecture of obesity.

OBJECTIVE: In the present study, we sought to identify causal relationships between obesity and other complex traits and conditions using a data-driven hypothesis-free approach that uses genetic data to infer causal associations. METHODS: We leveraged available summary-based genetic data from genome-wide association studies on 1498 phenotypes and applied the latent causal variable method (LCV) between obesity and all traits. RESULTS: We identified 110 traits causally associated with obesity. Of those, 109 were causal outcomes of obesity, while only leg pain in calves was a causal determinant of obesity. Causal outcomes of obesity included 26 phenotypes associated with cardiovascular diseases, 22 anthropometric measurements, nine with the musculoskeletal system, nine with behavioural or lifestyle factors including loneliness or isolation, six with respiratory diseases, five with body bioelectric impedances, four with psychiatric phenotypes, four related to the nervous system, four with disabilities or long-standing illness, three with the gastrointestinal system, three with use of analgesics, two with metabolic diseases, one with inflammatory response and one with the neurodevelopmental disorder ADHD, among others. In particular, some causal outcomes of obesity included hypertension, stroke, ever having a period of extreme irritability, low forced vital capacity and forced expiratory volume, diseases of the musculoskeletal system, diabetes, carpal tunnel syndrome, loneliness or isolation, high leukocyte count, and ADHD. CONCLUSIONS: Our results indicate that obesity causally affects a wide range of traits and comorbid diseases, thus providing an overview of the metabolic, physiological, and neuropsychiatric impact of obesity on human health.

Evidence of Genetic Overlap Between Circadian Preference and Brain White Matter Microstructure.

Several neuroimaging studies have reported associations between brain white matter microstructure and chronotype. However, it is unclear whether those phenotypic relationships are causal or underlined by genetic factors. In the present study, we use genetic data to examine the genetic overlap and infer causal relationships between chronotype and diffusion tensor imaging (DTI) measures. We identify 29 significant pairwise genetic correlations, of which 13 also show evidence for a causal association. Genetic correlations were identified between chronotype and brain-wide mean, axial and radial diffusivities. When exploring individual tracts, 10 genetic correlations were observed with mean diffusivity, 10 with axial diffusivity, 4 with radial diffusivity and 2 with mode of anisotropy. We found evidence for a possible causal association of eveningness with white matter microstructure measures in individual tracts including the posterior limb and the retrolenticular part of the internal capsule; the genu and splenium of the corpus callosum and the posterior, superior and anterior regions of the corona radiata. Our findings contribute to the understanding of how genes influence circadian preference and brain white matter and provide a new avenue for investigating the role of chronotype in health and disease.

Genetic Susceptibility to Pneumonia: A GWAS Meta-Analysis Between the UK Biobank and FinnGen.

Pneumonia is a respiratory condition with complex etiology. Host genetic variation is thought to contribute to individual differences in susceptibility and symptom manifestation. Here, we analyze pneumonia data from the UK Biobank (14,780 cases and 439,096 controls) and FinnGen (9980 cases and 86,519 controls) and perform a genomewide association study meta-analysis. We use gene-based tests, colocalization, genetic correlation, latent causal variable (LCV) and polygenic prediction in an independent Australian sample (N = 5595) to draw insights into the etiology of pneumonia risk. We identify two independent loci on chromosome 15 (lead single-nucleotide polymorphisms rs2009746 and rs76474922) to be associated with pneumonia (p < 5e-8). Gene-based tests revealed 18 genes in chromosomes 15, 16 and 9, including IL127, PBX3, ApoB receptor (APOBR) and smoking related genes CHRNA3/5, statistically associated with pneumonia. We observed genetic correlations between pneumonia and cardiorespiratory, psychiatric and inflammatory related traits. LCV analysis suggests a strong genetic causal relationship with cardiovascular health phenotypes. Polygenic risk scores for pneumonia significantly predicted self-reported pneumonia in an independent sample, albeit with a small effect size (OR = 1.11 95% CI [1.04, 1.19], p < .05). Sensitivity analyses suggested the associations in chromosome 15 are mediated by smoking history, but the associations in chromosomes 16 and 9, and polygenic prediction were robust to adjustment for smoking. Altogether, our results highlight common genetic variants, genes and potential pathways that contribute to individual differences in susceptibility to pneumonia, and advance our understanding of the genetic factors underlying heterogeneity in respiratory medical outcomes.

Phenome-wide analysis highlights putative causal relationships between self-reported migraine and other complex traits.

BACKGROUND: Migraine is a complex neurological disorder that is considered the most common disabling brain disorder affecting 14 % of people worldwide. The present study sought to infer potential causal relationships between self-reported migraine and other complex traits, using genetic data and a hypothesis-free approach. METHODS: We leveraged available summary statistics from genome-wide association studies (GWAS) of 1,504 phenotypes and self-reported migraine and inferred pair-wise causal relationships using the latent causal variable (LCV) method. RESULTS: We identify 18 potential causal relationships between self-reported migraine and other complex traits. Hypertension and blood clot formations were causally associated with an increased migraine risk, possibly through vasoconstriction and platelet clumping. We observed that sources of abdominal pain and discomfort might influence a higher risk for migraine. Moreover, occupational and environmental factors such as working with paints, thinner or glues, and being exposed to diesel exhaust were causally associated with higher migraine risk. Psychiatric-related phenotypes, including stressful life events, increased migraine risk. In contrast, ever feeling unenthusiastic / disinterested for a whole week, a phenotype related to the psychological well-being of individuals, was a potential outcome of migraine. CONCLUSIONS: Overall, our results suggest a potential vascular component to migraine, highlighting the role of vasoconstriction and platelet clumping. Stressful life events and occupational variables potentially influence a higher migraine risk. Additionally, a migraine could impact the psychological well-being of individuals. Our findings provide novel testable hypotheses for future studies that may inform the design of new interventions to prevent or reduce migraine risk and recurrence.

Suicidal ideation and planning among Mexican adolescents are associated with depression polygenic risk scores.

Suicide is a major public health problem in Mexico and around the world. Genetic predisposition for major depressive disorder (MDD) has been associated with increased risk for suicidal behaviors (SB) in populations of European ancestry (EA). Here, we examine whether MDD polygenic risk scores (MDD PRS), derived from a genome-wide association study involving EA individuals, predict SB, including ideation, planning, and attempt, among Mexican youth using a longitudinal design. At baseline, participants (N = 1,128, 12-17 years, 55% women) were interviewed and genotyped as part of a general population survey on adolescent mental health. Eight years later, they were recontacted for a follow up visit (N = 437, 20-25 years, 63% women). At both assessments, individuals reported on their engagement in SB within the past year. MDD PRS were significantly positively associated with SB, particularly suicide ideation and planning during adolescence, accounting for ~4-5% of the variance in these outcomes. In contrast, associations between MDD PRS and SB during young adulthood did not reach statistical significance. Our results suggest that increased genetic liability for depression increased risk for SB, particularly during adolescence, expanding our knowledge of the genetic underpinnings of SB.

Impact of genetic predisposition to late-onset neurodegenerative diseases on early life outcomes and brain structure.

Most patients with late-onset neurodegenerative diseases such as Alzheimer's and Parkinson's have a complex aetiology resulting from numerous genetic risk variants of small effects located across the genome, environmental factors, and the interaction between genes and environment. Over the last decade, genome-wide association studies (GWAS) and post-GWAS analyses have shed light on the polygenic architecture of these diseases, enabling polygenic risk scores (PRS) to estimate an individual's relative genetic liability for presenting with the disease. PRS can screen and stratify individuals based on their genetic risk, potentially years or even decades before the onset of clinical symptoms. An emerging body of evidence from various research studies suggests that genetic susceptibility to late-onset neurodegenerative diseases might impact early life outcomes, including cognitive function, brain structure and function, and behaviour. This article summarises recent findings exploring the potential impact of genetic susceptibility to neurodegenerative diseases on early life outcomes. A better understanding of the impact of genetic susceptibility to neurodegenerative diseases early in life could be valuable in disease screening, detection, and prevention and in informing treatment strategies before significant neural damage has occurred. However, ongoing studies have limitations. Overall, our review found several studies focused on APOE haplotypes and Alzheimer's risk, but a limited number of studies leveraging polygenic risk scores or focused on genetic susceptibility to other late-onset conditions.

Investigating the Shared Genetic Etiology Between Parkinson's Disease and Depression.

Background: Depression is a common symptom in Parkinson's disease (PD), resulting from underlying neuropathological processes and psychological factors. However, the extent to which shared genetic risk factors contribute to the relationship between depression and PD is poorly understood. Objective: To examine the effects of common genetic variants influencing the etiology of PD and depression risk at the genome-wide and local genomic regional level. Methods: We comprehensively investigated the genetic relationship between PD and depression using genome-wide association studies data. First, we estimated the genetic correlation at the genome-wide level using linkage-disequilibrium score regression, followed by local genetic correlation analysis using the GWAS-pairwise method and functional annotation to identify genes that may jointly influence the risk for both traits. Also, we performed Latent Causal Variable, Latent Heritable Confounder Mendelian Randomization, and traditional Mendelian Randomization analyses to investigate the potential causal relationship. Results: Although the genetic correlation between PD and depression was not statistically significant at the genome-wide level, GWAS-pairwise analyses identified 16 genomic segments associated with PD and depression, implicating nine genes. Further analyses revealed distinct patterns within individual genes, suggesting an intricate pattern. These genes involve various biological processes, including neurotransmitter regulation, senescence, and nucleo-cytoplasmic transport mechanisms. We did not observe genetic evidence of causality between PD and depression. Conclusions: Our findings did not support a genome-wide genetic correlation or a causal association between both conditions. However, we identified genomic segments but identified genomic segments linked to distinct biological pathways influencing their etiology.Further research is needed to understand their functional consequences.

Associations of externalizing polygenic scores with externalizing disorders among Mexican youth.

Several studies have examined the association of externalizing polygenic scores (PGS) with externalizing symptoms in samples of European ancestry. However, less is known about the associations of externalizing polygenic vulnerability in relation to phenotypic externalizing disorders among individuals of different ancestries, such as Mexican youth. Here, we leveraged the largest genome-wide association study on externalizing behaviors that included over 1 million individuals of European ancestry to examine associations of externalizing PGS with a range of externalizing disorders in Mexican adolescents, and investigated whether adversity exposure in childhood moderated these associations. Participants (N = 1064; age range 12-17 years old; 58.8% female) were adolescents recruited for a general population survey on adolescent mental health in the Mexico City Metropolitan region and were genotyped. Childhood adversity exposure and externalizing disorders, specifically attention-deficit hyperactivity disorder (ADHD), conduct disorder, oppositional defiant disorder, and substance use disorder, were assessed via the computer-assisted World Mental Health Composite International Diagnostic Interview for adolescents. A greater externalizing PGS was associated with a greater odds of any externalizing disorder (OR = 1.29 [1.12, 1.48]; p < 0.01) and ADHD (OR = 1.40 [1.15, 1.70]; p < 0.01) in the whole sample, and in females in particular. There were no main effects of the externalizing PGS on conduct disorder, oppositional defiant disorder, or substance use disorder, nor did adversity exposure moderate these associations. Our results suggest that greater genetic propensity for externalizing disorders is associated with increased odds of any externalizing disorders and ADHD among Mexican adolescents, furthering our understanding of externalizing disorder manifestation in this population.

Uncovering genetic loci and biological pathways associated with age-related cataracts through GWAS meta-analysis.

Age-related cataracts is a highly prevalent eye disorder that results in the clouding of the crystalline lens and is one of the leading causes of visual impairment and blindness. The disease is influenced by multiple factors including genetics, prolonged exposure to ultraviolet radiation, and a history of diabetes. However, the extent to which each of these factors contributes to the development of cataracts remains unclear. Our study identified 101 independent genome-wide significant loci, 57 of which are novel. We identified multiple genes and biological pathways associated with the cataracts, including four drug-gene interactions. Our results suggest a causal association between type 1 diabetes and cataracts. Also, we highlighted a surrogate measure of UV light exposure as a marker of cataract risk in adults.

Genome-wide meta-analyses of non-response to antidepressants identify novel loci and potential drugs.

Antidepressants exhibit a considerable variation in efficacy, and increasing evidence suggests that individual genetics contribute to antidepressant treatment response. Here, we combined data on antidepressant non-response measured using rating scales for depressive symptoms, questionnaires of treatment effect, and data from electronic health records, to increase statistical power to detect genomic loci associated with non-response to antidepressants in a total sample of 135,471 individuals prescribed antidepressants. We performed genome-wide association meta-analyses, leave-one-out polygenic prediction, and bioinformatics analyses for genetically informed drug prioritization. We identified two novel loci associated with non-response to antidepressants and showed significant polygenic prediction in independent samples. In addition, we investigated drugs that target proteins likely involved in mechanisms underlying antidepressant non-response, and shortlisted drugs that warrant further replication and validation of their potential to reduce depressive symptoms in individuals who do not respond to first-line antidepressant medications. These results suggest that meta-analyses of GWAS utilizing real-world measures of treatment outcomes can increase sample sizes to improve the discovery of variants associated with non-response to antidepressants.

Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries.

Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. We performed GWAS meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and, for the first time, the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signalling and brain ageing-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson's disease and ADHD. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases.

Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries.

Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. Here we performed genome-wide association studies meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signaling and brain aging-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson's disease and attention-deficit/hyperactivity disorder. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases.

Causal associations of sleep apnea and snoring with type 2 diabetes and glycemic traits and the role of BMI.

OBJECTIVE: Sleep apnea and snoring have been associated with type 2 diabetes, with BMI playing a role in the pathway, but the directions of causality are unclear. This study examined the causal associations of sleep apnea and snoring with type 2 diabetes while assessing the role of BMI using multiple genetic methods. METHODS: Five genetic methods were used: two-sample; bidirectional univariable Mendelian randomization (MR) inverse variance-weighted (MR-IVW); multivariable MR-IVW; network MR; and latent causal variable method. RESULTS: Compared with univariable MR-IVW, the odds ratio (95% CI) of type 2 diabetes for genetically predicted sleep apnea and snoring using the largest genome-wide association study decreased dramatically, from 1.61 (95% CI: 1.16-2.23) to 1.08 (95% CI: 0.59-1.97) and from 1.98 (95% CI: 1.25-3.13) to 1.09 (95% CI: 0.64-1.86) after adjustment for BMI. Network MR showed that BMI accounts for 67% and 62% of the total effect of sleep apnea and snoring on type 2 diabetes, respectively. The latent causal variable suggested that sleep apnea and snoring have no direct causal effect on type 2 diabetes. CONCLUSIONS: These results first suggest that the associations of sleep apnea and snoring with type 2 diabetes were mainly driven by BMI. The possible indirect effects of sleep apnea and snoring on type 2 diabetes through BMI cannot be ruled out.