Polygenic liability for anxiety in association with comorbid anxiety in multiple sclerosis.

OBJECTIVE: Comorbid anxiety occurs often in MS and is associated with disability progression. Polygenic scores offer a possible means of anxiety risk prediction but often have not been validated outside the original discovery population. We aimed to investigate the association between the Generalized Anxiety Disorder 2-item scale polygenic score with anxiety in MS. METHODS: Using a case-control design, participants from Canadian, UK Biobank, and United States cohorts were grouped into cases (MS/comorbid anxiety) or controls (MS/no anxiety, anxiety/no immune disease or healthy). We used multiple anxiety measures: current symptoms, lifetime interview-diagnosed, and lifetime self-report physician-diagnosed. The polygenic score was computed for current anxiety symptoms using summary statistics from a previous genome-wide association study and was tested using regression. RESULTS: A total of 71,343 individuals of European genetic ancestry were used: Canada (n = 334; 212 MS), UK Biobank (n = 70,431; 1,390 MS), and the USA (n = 578 MS). Meta-analyses identified that in MS, each 1-SD increase in the polygenic score was associated with ~50% increased odds of comorbid moderate anxious symptoms compared to those with less than moderate anxious symptoms (OR: 1.47, 95% CI: 1.09-1.99). We found a similar direction of effects in the other measures. MS had a similar anxiety genetic burden compared to people with anxiety as the index disease. INTERPRETATION: Higher genetic burden for anxiety was associated with significantly increased odds of moderate anxious symptoms in MS of European genetic ancestry which did not differ from those with anxiety and no comorbid immune disease. This study suggests a genetic basis for anxiety in MS.

Metabolic profiling of smoking, associations with type 2 diabetes and interaction with genetic susceptibility.

BACKGROUND: Smokers are at increased risk of type 2 diabetes (T2D), but the underlying mechanisms are unclear. We investigated if the smoking-T2D association is mediated by alterations in the metabolome and assessed potential interaction with genetic susceptibility to diabetes or insulin resistance. METHODS: In UK Biobank (n = 93,722), cross-sectional analyses identified 208 metabolites associated with smoking, of which 131 were confirmed in Mendelian Randomization analyses, including glycoprotein acetyls, fatty acids, and lipids. Elastic net regression was applied to create a smoking-related metabolic signature. We estimated hazard ratios (HR) of incident T2D in relation to baseline smoking/metabolic signature and calculated the proportion of the smoking-T2D association mediated by the signature. Additive interaction between the signature and genetic risk scores for T2D (GRS-T2D) and insulin resistance (GRS-IR) on incidence of T2D was assessed as relative excess risk due to interaction (RERI). FINDINGS: The HR of T2D was 1·73 (95% confidence interval (CI) 1·54 - 1·94) for current versus never smoking, and 38·3% of the excess risk was mediated by the metabolic signature. The metabolic signature and its mediation role were replicated in TwinGene. The metabolic signature was associated with T2D (HR: 1·61, CI 1·46 - 1·77 for values above vs. below median), with evidence of interaction with GRS-T2D (RERI: 0·81, CI: 0·23 - 1·38) and GRS-IR (RERI 0·47, CI: 0·02 - 0·92). INTERPRETATION: The increased risk of T2D in smokers may be mediated through effects on the metabolome, and the influence of such metabolic alterations on diabetes risk may be amplified in individuals with genetic susceptibility to T2D or insulin resistance.

Effects from medications on functional biomarkers of aging in three longitudinal studies of aging in Sweden.

Antihypertensive, lipid-lowering, and blood glucose-lowering drugs have slowed down the aging process in animal models. In humans, studies are limited, have short follow-up times, and show mixed results. Therefore, this study aimed to estimate the effects of commonly used medications on functional aging, cognitive function, and frailty. We included information on individuals from three Swedish longitudinal population-based studies collected between 1986 and 2014. Our exposures were the 21 most used groups of medications among individuals aged 65 years and older in the Swedish population in 2022. Functional aging index (n = 1191), cognitive function (n = 1094), and frailty index (n = 1361) were the outcomes of interest. To estimate the medication effects, we used a self-controlled analysis, where each individual is his/her own control, thereby adjusting for all time-stable confounders. The analysis was additionally adjusted for time-varying confounders (chronological age, Charlson Comorbidity Index, smoking, body mass index, and the number of drugs). The participants were 65.5-82.8 years at the first in-person assessment. Adrenergics/inhalants (effect size = 0.089) and lipid-modifying agents/plain (effect size = 0.082) were associated with higher values of cognitive function (improvement), and selective calcium channel blockers with mainly vascular effects (effect size = -0.129) were associated with lower values of the functional aging index (improvement). No beneficial effects were found on the frailty index. Adrenergics/inhalants, lipid-modifying agents/plain, and selective calcium channel blockers with mainly vascular effects may benefit functional biomarkers of aging. More research is needed to investigate their clinical value in preventing adverse aging outcomes.

Epigenome-wide analysis of frailty: Results from two European twin cohorts.

Epigenetics plays an important role in the aging process, but it is unclear whether epigenetic factors also influence frailty, an age-related state of physiological decline. In this study, we performed a meta-analysis of epigenome-wide association studies in four samples drawn from the Swedish Adoption/Twin Study of Aging (SATSA) and the Longitudinal Study of Aging Danish Twins (LSADT) to explore the association between DNA methylation and frailty. Frailty was defined using the frailty index (FI), and DNA methylation levels were measured in whole blood using Illumina's Infinium HumanMethylation450K and MethylationEPIC arrays. In the meta-analysis consisting of a total of 829 participants, we identified 589 CpG sites that were statistically significantly associated with either the continuous or categorical FI (false discovery rate <0.05). Many of these CpGs have previously been associated with age and age-related diseases. The identified sites were also largely directionally consistent in a longitudinal analysis using mixed-effects models in SATSA, where the participants were followed up to a maximum of 20 years. Moreover, we identified three differentially methylated regions within the MGRN1, MIR596, and TAPBP genes that have been linked to neuronal aging, tumor growth, and immune functions. Furthermore, our meta-analysis results replicated 34 of the 77 previously reported frailty-associated CpGs at p < 0.05. In conclusion, our findings demonstrate robust associations between frailty and DNA methylation levels in 589 novel CpGs, previously unidentified for frailty, and strengthen the role of neuronal/brain pathways in frailty.

Validation of biomarkers of aging.

The search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve as surrogate endpoints for the evaluation of interventions promoting healthy aging and longevity. However, no consensus exists on how biomarkers of aging should be validated before their translation to the clinic. Here, we review current efforts to evaluate the predictive validity of omic biomarkers of aging in population studies, discuss challenges in comparability and generalizability and provide recommendations to facilitate future validation of biomarkers of aging. Finally, we discuss how systematic validation can accelerate clinical translation of biomarkers of aging and their use in gerotherapeutic clinical trials.

Associations between Sleep Disorders and Impulsive-Compulsive Behaviors in Parkinson's Disease: A Prospective Cohort Study.

OBJECTIVE: To examine the associations of excessive daytime sleepiness (EDS) and probable rapid eye movement sleep behavior disorder (pRBD), respectively, with impulsive-compulsive behaviors (ICB) over a 5-year follow-up in patients with early Parkinson's disease (PD). METHODS: The Parkinson's Progression Markers Initiative is a multicenter cohort study based on an ongoing and open-ended registry. Longitudinal associations of sleep disorders with ICB over 5-year follow-up visits were estimated using generalized linear mixed-effects models among PD participants. RESULTS: A total of 825 PD participants were enrolled at baseline. The study sample had a median baseline age of 63.1 (interquartile range [IQR]: 55.6-69.3) years and comprised 496 (61.5%) men. Among them, 201 (24.9%) had ICB at baseline. In the generalized mixed-effects models, EDS (odds ratio [OR] =1.09, 95% confidence interval [CI] 1.05, 1.12) and RBD (OR=1.07, 95% CI 1.03, 1.12) were substantially associated with higher odds of developing ICB over time in PD patients, after multivariate adjustment including age, gender, family history, GDS score, STAI-Y score, MDS-UPDRS part III score, LEDD, and disease duration. Consistent results were observed when stratifying by age at baseline, gender, and PD family history. CONCLUSIONS: The study findings suggest a longitudinal association between EDS and pRBD with an increased risk of developing ICB in patients with Parkinson's disease. The findings emphasize the significance of evaluating and addressing sleep disorders in PD patients as a potential approach to managing ICB.

Genetically determined telomere length and its association with chronic obstructive pulmonary disease and interstitial lung disease in biobank Japan: A Mendelian randomization study.

Importance: Chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) have been linked to shorter telomere length (TL). While understanding this association has critical clinical implications for respiratory diseases, previous studies exploring these associations were conducted in European populations. The present study aims to investigate this relationship in an Asian population. Objective: To examine the causal relationship between leukocyte TL and COPD and ILD in an Asian population. Design: Setting, and Participants: We used a genome-wide association study summary statistics-based two-sample Mendelian randomization (MR) design to investigate the association between leukocyte TL, genetically predicted by nine single-nucleotide polymorphisms and the risk of COPD and ILD. Participants were Japanese individuals enrolled in the Biobank Japan Project, including 3315 COPD patients and 806 ILD patients. Exposure: Leukocyte TL was genetically predicted by nine single-nucleotide polymorphisms. Results: The inverse-variance weighted estimates showed a significant inverse association between leukocyte TL and COPD (odds ratio [OR] = 0.78; 95 % confidence interval [CI]: 0.64, 0.95; P = 0.01) and ILD (OR = 0.29; 95 % CI: 0.14, 0.61; P = 0.001), respectively. All sensitivity analyses yielded consistent results. The MR-Egger regression intercept test showed no evidence of horizontal pleiotropy (Pintercept: COPD, 0.56; ILD: 0.70). Conclusion: and Relevance: Our findings suggest that leukocyte telomere shortening may causally increase the risk of COPD and ILD. These results highlight the potential importance of TL for these respiratory diseases.

Combining Mendelian randomization with the sibling comparison design.

Mendelian randomization (MR) is a popular epidemiologic study design that uses genetic variants as instrumental variables (IVs) to estimate causal effects, while accounting for unmeasured confounding. The validity of the MR design hinges on certain IV assumptions, which may sometimes be violated due to dynastic effects, population stratification, or assortative mating. Since these mechanisms act through parental factors it was recently suggested that the bias resulting from violations of the IV assumptions can be reduced by combing the MR design with the sibling comparison design, which implicitly controls for all factors that are constant within families. In this article, we provide a formal discussion of this combined MR-sibling design. We derive conditions under which the MR-sibling design is unbiased, and we relate these to the corresponding conditions for the standard MR and sibling comparison designs. We proceed by considering scenarios where all three designs are biased to some extent, and discuss under which conditions the MR-sibling design can be expected to have less bias than the other two designs. We finally illustrate the theoretical results and conclusions with an application to real data, in a study of low-density lipoprotein and diastolic blood pressure using data from the Swedish Twin Registry.

Distinct genomic signatures and modifiable risk factors underly the comorbidity between major depressive disorder and cardiovascular disease.

Major depressive disorder (MDD) and cardiovascular disease (CVD) are often comorbid, resulting in excess morbidity and mortality. Using genomic data, this study elucidates biological mechanisms, key risk factors, and causal pathways underlying their comorbidity. We show that CVDs share a large proportion of their genetic risk factors with MDD. Multivariate genome-wide association analysis of the shared genetic liability between MDD and atherosclerotic CVD (ASCVD) revealed seven novel loci and distinct patterns of tissue and brain cell-type enrichments, suggesting a role for the thalamus. Part of the genetic overlap was explained by shared inflammatory, metabolic, and psychosocial/lifestyle risk factors. Finally, we found support for causal effects of genetic liability to MDD on CVD risk, but not from most CVDs to MDD, and demonstrated that the causal effects were partly explained by metabolic and psychosocial/lifestyle factors. The distinct signature of MDD-ASCVD comorbidity aligns with the idea of an immunometabolic sub-type of MDD more strongly associated with CVD than overall MDD. In summary, we identify plausible biological mechanisms underlying MDD-CVD comorbidity, as well as key modifiable risk factors for prevention of CVD in individuals with MDD.

Associations between psychological resilience and epigenetic clocks in the health and retirement study.

The aim of this study was to evaluate the associations between psychological resilience and epigenetic clocks assessed by DNA methylation age predictions. We used data from 4018 participants in the Health and Retirement Study. Multivariable linear regression models were used to estimate the association between psychological resilience and epigenetic clocks adjusted for age, sex, race, body mass index, smoking status, and years of education. Thirteen epigenetic clocks were used in our analysis and were highly correlated with one another. A higher psychological resilience score was associated with slower DNA methylation age acceleration for the majority of epigenetic clocks after multivariable adjustment. These findings imply that people with a higher level of psychological resilience may experience slower DNA methylation age acceleration and biological aging.

Clinical biomarker-based biological ageing and future risk of neurological disorders in the UK Biobank.

BACKGROUND: Many common neurological disorders are associated with advancing chronological age, but their association with biological age (BA) remains poorly understood. METHODS: We studied 325 870 participants in the UK Biobank without a diagnosed neurological condition at baseline and generated three previously-described measures of BA based on 18 routinely measured clinical biomarkers (PhenoAge, Klemera-Doubal method age (KDMAge), homeostatic dysregulation age). Using survival models, we assessed the effect of advanced BA on incident neurological diagnoses, including all-cause and cause-specific dementia, ischaemic stroke, Parkinson's disease and motor neuron disease. RESULTS: During a mean follow-up of 9.0 years, there were 1397 incident cases of dementia and 2515 of ischaemic stroke, with smaller case numbers of other diagnoses. The strongest associations with a 1 SD in BA residual were seen for all-cause dementia (KDMAge HR=1.19, 95% CI=1.11 to 1.26), vascular dementia (1.41, 1.25 to 1.60) and ischaemic stroke (1.39, 1.34 to 1.46). Weaker associations were seen for Alzheimer's disease and motor neuron disease, while, in contrast, HRs for Parkinson's disease tended to be <1. Results were largely consistent after adjustment for disease-specific covariates including common cardiometabolic risk factors. CONCLUSIONS: Advanced BA calculated from routine clinical biomarker results increases the risk of subsequent neurological diagnoses including all-cause dementia and ischaemic stroke.

Kidney Function Measures and Mortality: A Mendelian Randomization Study.

RATIONALE & OBJECTIVE: Individuals with a low estimated glomerular filtration rate (eGFR) are at a high risk of death. However, the causes underpinning this association are largely uncertain. This study aimed to assess the causal relationship of low eGFR with all-cause and cause-specific mortality. STUDY DESIGN: Retrospective cohort study incorporating Mendelian randomization (MR). SETTING & PARTICIPANTS: Individual-level data from 436,214 White participants (54.3% female; aged 56.8±8.0 years) included in the UK Biobank. EXPOSURES: eGFR estimated using cystatin C (eGFRcyst). OUTCOMES: The outcomes of interest included all-cause mortality, cardiovascular mortality, cancer mortality, infection mortality, and other-cause mortality. ANALYTICAL APPROACH: Cox proportional hazards analysis for the conventional observational analyses; linear and nonlinear MR analyses implemented using genetic allele scores as instrumental variables representing kidney function to estimate the effect of kidney function on the survival outcomes. RESULTS: During a median follow-up of 12.1 years, there were 30,489 deaths, 6,098 of which were attributed to cardiovascular events, 15,538 to cancer, 1,516 to infection, and 7,227 to other events. In the conventional observational analysis, eGFRcyst exhibited a nonlinear association with all the outcomes. MR analysis suggested that a genetically predicted lower eGFRcyst was linearly associated with a higher rate of cardiovascular mortality (HR, 1.43; 95% CI, 1.18-1.75) across the entire measurement range (every 10-mL/min/1.73m2 decrement). Nonetheless, no causal associations between eGFRcyst and all-cause mortality (HR, 1.07; 95% CI, 0.98-1.17) or any types of noncardiovascular mortality were detected. LIMITATIONS: Potential misclassification of the actual cause of death, a nonrepresentative sample, and potential error in the interpretation of the magnitude of associations generated in MR analyses. CONCLUSIONS: These findings suggest a potential causal association between low eGFR and cardiovascular mortality in the general population, but no causal relationship with all-cause mortality or noncardiovascular mortality was observed. Further studies in other populations are warranted to confirm these findings. PLAIN-LANGUAGE SUMMARY: This study investigated the existence of a causal relationship between lower kidney function and death of different causes. Using data from 436,214 people in the United Kingdom, we applied conventional statistical analyses and those incorporating genetic data to implement Mendelian randomization, an approach that estimates causal associations. The observational analysis showed a nonlinear association between kidney function and various types of mortality outcomes. However, Mendelian randomization analysis suggested a linear increase in the risk of cardiovascular mortality with lower kidney function, but no causal link between the level of kidney function and all-cause or noncardiovascular mortality was identified. Managing kidney health may help reduce cardiovascular mortality, but caution is needed in interpreting the magnitudes of these results. Further validation in other populations and in those with advanced kidney failure is needed.

Anticoagulant treatment and COVID-19 mortality among older adults living in nursing homes in Sweden.

Background: Anticoagulants (AC) were introduced in March 2020 as standard of care in nursing home (NH) residents affected with COVID-19 in the Stockholm region, Sweden. ACs are proven to reduce the risk of complications and mortality from COVID-19 among patients of other ages and settings, but there is limited scientific evidence underpinning this practice in the NH setting. Methods: This matched cohort study included 182 NH residents in the Stockholm Region diagnosed with COVID-19 in March-May 2020. The main exposure was any AC treatment. Exposed (n = 91), 49% prevalent (pre-COVID-19 diagnosis) AC and 51% incident AC were compared with unexposed controls (n = 91). The outcome was 28-days all-cause mortality after COVID-19 infection. The mortality odds ratios (OR) were assessed using logistic regression, adjusted for age, sex, multimorbidity, and mobility, also stratified by incident or prevalent AC-type, age group, and sex. Results: Of the 182 individuals diagnosed with COVID-19 (median age 88 years, 68% women), 39% died within 28 days after diagnosis. Use of either incident or prevalent AC was associated with a reduced, adjusted 28-day mortality (OR[95% CI]: 0.31[0.16-0.62]). In stratified analyses, the association was significant in both age groups: 70-89 (OR: 0.37 [0.15-0.89]) and 90-99 years of age (OR: 0.22 [0.07-0.65]. In sex-stratified analysis, the AC-lowering effect was significant in women only (OR: 0.28[0.11-0.67]). In the analyses stratified by AC type, the mortality-lowering effect was observed for both prevalent AC (OR: 0.35[0.12-0.99]) and incident AC (OR: 0.29[0.11-0.76]). Conclusions: Both prevalent and incident use of ACs in prophylactic dosing was associated with reduced 28-day mortality among older individuals with COVID-19 in a NH setting. The effect was seen across age-strata and in women. The findings present new insight in best practice for individuals diagnosed with COVID-19 in the NH setting.

Temporal dynamics of epigenetic aging and frailty from midlife to old age.

BACKGROUND: DNA methylation-derived epigenetic clocks and frailty are well-established biological age measures capturing different aging processes. However, whether they are dynamically linked to each other across chronological age remains poorly understood. METHODS: This analysis included 1,309 repeated measurements in 524 individuals aged 50 to 90 years from the Swedish Adoption/Twin Study of Aging. Frailty was measured using a validated 42-item frailty index (FI). Five epigenetic clocks were calculated, including four principal component (PC)-based clocks trained on chronological age (PCHorvathAge, PCHannumAge) and aging-related physiological conditions (PCPhenoAge, PCGrimAge), and a pace of aging clock (DunedinPACE). Using dual change score models, we examined the dynamic, bidirectional associations between each of the epigenetic clocks and the FI over age to test for potential causal associations. RESULTS: The FI exhibited a nonlinear, accelerated increase across the older adulthood, whereas the epigenetic clocks mostly increased linearly with age. For PCHorvathAge, PCHannumAge, PCPhenoAge, and PCGrimAge, their associations with the FI were primarily due to correlated levels at age 50 but with no evidence of a dynamic longitudinal association. In contrast, we observed a unidirectional association between DunedinPACE and the FI, where a higher DunedinPACE predicted a subsequent increase in the FI, but not vice versa. CONCLUSION: Our results highlight a temporal order between epigenetic aging and frailty such that changes in DunedinPACE precede changes in the FI. This potentially suggests that the pace of aging clock can be used as an early marker of the overall physiological decline at system level.

Is Frailty Different in Younger Adults Compared to Old? Prevalence, Characteristics, and Risk Factors of Early-Life and Late-Life Frailty in Samples from Sweden and UK.

INTRODUCTION: Although frailty is commonly considered as a syndrome of old individuals, recent studies show that it can affect younger adults, too. Whether and how frailty differs in younger adults compared to old is however unknown. To this end, we analyzed the prevalence, characteristics, and risk factors of early-life (aged <65) and late-life (aged ≥65) frailty. METHODS: We analyzed individuals in the UK Biobank (N = 405,123) and Swedish Screening Across the Lifespan Twin (SALT; N = 43,641) study. Frailty index (FI) scores ≥0.21 were used to demarcate frailty. Characteristics of early-life versus late-life frailty were analyzed by collating the FI items (deficits) into domains and comparing the domain scores between younger and older frail individuals. Logistic regression was used to assess the risk factors of frailty. RESULTS: The pooled prevalence rates of frailty were 10.3% (95% confidence interval [CI]: 2.7-32.7), 14.4% (95% CI: 4.5-37.2), 19.2% (95% CI: 2.5-68.5) in individuals aged ≤55, 55-64, 65-74, respectively. Younger frail adults (aged <65) had higher scores in immunological, mental wellbeing, and pain-related domains, whereas older frail adults (aged ≥65) had higher scores in cardiometabolic, cancer, musculoskeletal, and sensory-related domains. Higher age, female sex, smoking, lower alcohol consumption, lower education, obesity, overweight, low income, and maternal smoking were similarly associated with the risk of early-life and late-life frailty. CONCLUSION: Frailty is prevalent also in younger age groups (aged <65) but differs in some of its characteristics from the old. The risk factors of frailty are nevertheless largely similar for early-life and late-life frailty.

Advanced biological ageing predicts future risk for neurological diagnoses and clinical examination findings.

Age is a dominant risk factor for some of the most common neurological diseases. Biological ageing encompasses interindividual variation in the rate of ageing and can be calculated from clinical biomarkers or DNA methylation data amongst other approaches. Here, we tested the hypothesis that a biological age greater than one's chronological age affects the risk of future neurological diagnosis and the development of abnormal signs on clinical examination. We analysed data from the Swedish Adoption/Twin Study of Aging (SATSA): a cohort with 3175 assessments of 802 individuals followed-up over several decades. Six measures of biological ageing were generated: two physiological ages (created from bedside clinical measurements and standard blood tests) and four blood methylation age measures. Their effects on future stroke, dementia or Parkinson's disease diagnosis, or development of abnormal clinical signs, were determined using survival analysis, with and without stratification by twin pairs. Older physiological ages were associated with ischaemic stroke risk; for example one standard deviation advancement in baseline PhenoAgePhys or KDMAgePhys residual increased future ischaemic stroke risk by 29.2% [hazard ratio (HR): 1.29, 95% confidence interval (CI) 1.06-1.58, P = 0.012] and 42.9% (HR 1.43, CI 1.18-1.73, P = 3.1 × 10-4), respectively. In contrast, older methylation ages were more predictive of future dementia risk, which was increased by 29.7% (HR 1.30, CI 1.07-1.57, P = 0.007) per standard deviation advancement in HorvathAgeMeth. Older physiological ages were also positively associated with future development of abnormal patellar or pupillary reflexes, and the loss of normal gait. Measures of biological ageing can predict clinically relevant pathology of the nervous system independent of chronological age. This may help to explain variability in disease risk between individuals of the same age and strengthens the case for trials of geroprotective interventions for people with neurological disorders.

Rare functional variants in the CRP and G6PC genes modify the relationship between obesity and serum C-reactive protein in white British population.

BACKGROUND: C-reactive protein (CRP) is a sensitive biomarker of inflammation with moderate heritability. The role of rare functional genetic variants in relation to serum CRP is understudied. We aimed to examine gene mutation burden of protein-altering (PA) and loss-of-function (LOF) variants in association with serum CRP, and to further explore the clinical relevance. METHODS: We included 161,430 unrelated participants of European ancestry from the UK Biobank. Of the rare (minor allele frequency <0.1%) and functional variants, 1,776,249 PA and 266,226 LOF variants were identified. Gene-based burden tests, linear regressions, and logistic regressions were performed to identify the candidate mutations at the gene and variant levels, to estimate the potential interaction effect between the identified PA mutation and obesity, and to evaluate the relative risk of 16 CRP-associated diseases. RESULTS: At the gene level, PA mutation burdens of the CRP (ß = -0.685, p = 2.87e-28) and G6PC genes (ß = 0.203, p = 1.50e-06) were associated with reduced and increased serum CRP concentration, respectively. At the variant level, seven PA alleles in the CRP gene decreased serum CRP, of which the per-allele effects were approximately three to seven times greater than that of a common variant in the same locus. The effects of obesity and central obesity on serum CRP concentration were smaller among the PA mutation carriers in the CRP (pinteraction = 0.008) and G6PC gene (pinteraction = 0.034) compared to the corresponding non-carriers. CONCLUSION: PA mutation burdens in the CRP and G6PC genes are strongly associated with decreased serum CRP concentrations. As serum CRP and obesity are important predictors of cardiovascular risks in clinics, our observations suggest taking rare genetic factors into consideration might improve the delivery of precision medicine.

Polygenicity of Comorbid Depression in Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: Depression is common in multiple sclerosis (MS) and is associated with faster disability progression. The etiology of comorbid depression in MS remains poorly understood. Identification of individuals with a high risk of depression, through polygenic scores (PGS), may facilitate earlier identification. Previous genetic studies of depression considered depression as a primary disorder, not a comorbidity, and thus, findings may not generalize to MS. Body mass index (BMI) is a risk factor of both MS and depression, and its association may highlight differences in depression in MS. To improve the understanding of comorbid depression in MS, we will investigate PGS in people with MS, with the hypothesis that a higher depression PGS is associated with increased odds for comorbid depression in MS. METHODS: Samples from 3 sources (Canada, UK Biobank, and the United States) were used. Individuals were grouped into cases (MS/comorbid depression) and compared with 3 control groups: MS/no depression, depression/no immune disease, and healthy persons. We used 3 depression definitions: lifetime clinical diagnoses, self-reported diagnoses, and depressive symptoms. The PGS were tested in association with depression using regression. RESULTS: A total of 106,682 individuals of European genetic ancestry were used: Canada (n = 370; 213 with MS), UK Biobank (n = 105,734; 1,390 with MS), and the United States (n = 578 with MS). Meta-analyses revealed individuals with MS and depression had a higher depression PGS compared with both individuals with MS without depression (odds ratio range per SD 1.29-1.38, p < 0.05) and healthy controls (odds ratio range per SD 1.49-1.53, p < 0.025), regardless of the definition applied and when sex stratified. The BMI PGS was associated with depressive symptoms (p ≤ 0.001). The depression PGS did not differ between depression occurring as a comorbid condition with MS or as the primary condition (odds ratio range per SD 1.03-1.13, all p > 0.05). DISCUSSION: A higher depression genetic burden was associated with approximately 30%-40% increased odds of depression in European genetic ancestry participants with MS compared with those without depression and was no different compared with those with depression and no comorbid immune disease. This study paves the way for further investigations into the possible use of PGS for assessing psychiatric disorder risk in MS and its application to non-European genetic ancestries.

Unraveling the metabolic underpinnings of frailty using multicohort observational and Mendelian randomization analyses.

Identifying metabolic biomarkers of frailty, an age-related state of physiological decline, is important for understanding its metabolic underpinnings and developing preventive strategies. Here, we systematically examined 168 nuclear magnetic resonance-based metabolomic biomarkers and 32 clinical biomarkers for their associations with frailty. In up to 90,573 UK Biobank participants, we identified 59 biomarkers robustly and independently associated with the frailty index (FI). Of these, 34 associations were replicated in the Swedish TwinGene study (n = 11,025) and the Finnish Health 2000 Survey (n = 6073). Using two-sample Mendelian randomization, we showed that the genetically predicted level of glycoprotein acetyls, an inflammatory marker, was statistically significantly associated with an increased FI (ß per SD increase = 0.37%, 95% confidence interval: 0.12-0.61). Creatinine and several lipoprotein lipids were also associated with increased FI, yet their effects were mostly driven by kidney and cardiometabolic diseases, respectively. Our findings provide new insights into the causal effects of metabolites on frailty and highlight the role of chronic inflammation underlying frailty development.