Lauren A. Vanderlinden

OBJECTIVE: Type 1 diabetes is half as common in offspring of mothers versus fathers with type 1 diabetes. We investigated whether selective loss of fetuses with high genetic risk during type 1 diabetes pregnancy explains this relative protection. RESEARCH DESIGN AND METHODS: In 6,942 live births in The Environmental Determinants of Diabetes in the Young (TEDDY) cohort, we compared genetic susceptibility by family member with type 1 diabetes and tested whether it explained maternal protection from diabetes or its preclinical stages. RESULTS: The type 1 diabetes Genetic Risk Score 2 extended (GRS2x) did not differ between children with mothers (P = 0.36) or siblings (P = 0.27) versus fathers with type 1 diabetes. Relative maternal protection from type 1 diabetes and islet autoimmunity (IA) was observed with GRS2x adjustment (diabetes: hazard ratio [HR] 0.50, P = 0.01; IA: HR 0.38, P = 0.006) and without adjustment but not during progression from IA to diabetes. This protection waned after age 6 years. CONCLUSIONS: Intrauterine exposure to type 1 diabetes offers relative protection from IA during early childhood and is not explained by genetic susceptibility differences.

Introduction: Seroconversion (SV) marks islet autoimmunity (IA) onset and preclinical type 1 diabetes (T1D), yet the contributions beyond T and B lymphocytes remain unclear. We evaluated DNA methylation (DNAm)-derived immune cell ratios between T1D cases and controls around SV. Research design and methods: High-resolution immune cell-type deconvolution of peripheral blood DNAm from nested case-control samples in the Diabetes Autoimmunity Study in the Young (DAISY; n=151) and the Environmental Determinants of Diabetes in the Young (TEDDY; n=166) estimated immune cell proportions at pre-SV (the latest visit before SV) and at SV (the first visit with persistent detected autoantibodies) to construct immune cell ratios, such as the neutrophil-to-lymphocyte ratio (NLR). Linear models compared T1D cases to matched T1D controls (IA negative) at pre-SV, SV, and the change across time points. Results: From pre-SV to SV, controls showed expected developmental increases in B-memory/naive, B-CD4T-CD8T memory/naive, and NLR, while cases failed to follow these patterns, with attenuated trajectories of 35%, 38%, and 21%, respectively. Pre-SV, cases had 15% higher NLR and 9% lower CD4T/CD8T. At SV, the combined B-CD4T-CD8T memory/naive ratio was 26% reduced in cases. Conclusions: These patterns may reflect increased neutrophil activation or pancreatic infiltration, altered CD4 and CD8 T cell balance, and delayed or disrupted immune maturation with the persistence or expansion of naive B and T cells or impaired transition to memory B and T subsets following antigen exposure. Our findings highlight early shifts in innate and adaptive immune cell dynamics during T1D pathogenesis and support methylation-derived immune cell ratios as potential biomarkers for risk stratification and mechanistic insight.

Longitudinal single-cell clinical studies enable tracking within-individual cellular dynamics, but methods for modeling temporal phenotypic changes and estimating power remain limited. We present scLASER, a framework detecting time-dependent cellular neighborhood dynamics and simulating longitudinal single-cell datasets for power estimation. Across benchmark experiments, scLASER shows consistently higher sensitivity than traditional cluster--based approaches, with particularly pronounced gains in rare cell types and non-linear temporal patterns. Applications to inflammatory bowel disease (95,813 cells, 38 patients) reveal treatment-responsive NOTCH3+ stromal trajectories with high cell type discrimination (AUC > 0.92), while analysis of COVID-19 data (188,181 cells, 84 patients) identifies three distinct axes of T cell activity (cytotoxic effector, NK immunoreceptor signaling, and interferon-stimulated gene programs) over disease progression. scLASER enables robust longitudinal single-cell analysis and optimization of study design. Teaser: A new framework detects time-dependent cellular dynamics and enables power estimation for longitudinal clinical single-cell studies.

Objective: Rheumatoid arthritis (RA) is a heterogeneous autoimmune disease characterized by clinical and molecular heterogeneity, notably in the presence of anti–cyclic citrullinated peptide (CCP) antibodies. Patients with CCP+ RA exhibit more severe disease progression and distinct treatment responses compared to patients with CCP− RA. Although previous studies have investigated cellular and molecular differences between these subtypes, their genetic differences are understudied. Methods: We leveraged the Rheumatoid Arthritis Comparative Effectiveness Research cohort, comprising 555 patients with CCP+/rheumatoid factor (RF)+ RA and 384 patients with CCP−/RF+ RA. Using a novel framework, we integrated a network‐based genome‐wide association study (GWAS) with multiomic data to uncover corresponding genetic and molecular differences. Results: We uncovered a significant heritability difference between these disease groups. Network‐based GWAS uncovered 14 putative gene modules, including many genes outside the HLA loci, that explained genetic differences between CCP+/RF+ and CCP−/RF+ RA. Heritability partitioning and multivariate expression analyses validated four modules, highlighting novel genetic loci underlying phenotypic differences. Module functional significance was established using multiple orthogonal cohorts, underscoring their biologic relevance. Conclusion: Our findings demonstrate the use of network‐based approaches in revealing differential genetic risk factors underlying CCP+/RF+ and CCP−/RF+ RA. Disease‐associated gene modules detected in synovial tissue were also observed in peripheral blood, indicating joint‐specific molecular programs are reflected systemically. This cross‐tissue concordance highlights the potential for blood‐based assays to capture pathogenic mechanisms active in the joints, enabling practical patient stratification. Our findings highlight why patients with CCP+/RF+ and CCP−/RF+ RA exhibit distinct clinical courses and therapeutic responses, supporting precision‐guided treatment strategy development in RA. image

Background: Type 1 diabetes is believed to be associated with early genetic and environmental stressors. Epigenetic age acceleration (EAA) is also associated with environmental stressors and the pathogenesis of many chronic diseases. This study explored longitudinal changes in EAA among individuals at high risk for type 1 diabetes. Methods: DNA methylation was measured longitudinally in subjects from the Diabetes Autoimmunity Study in the Young cohort, 2547 children born 1993–2006 at high risk for type 1 diabetes. Data were collected before and after islet autoimmunity (IA) seroconversion, a preclinical type 1 diabetes stage. EAA was estimated from DNA methylation using an epigenetic clock appropriate for pediatric blood samples. A linear mixed model was used to test for differences in EAA between 85 type 1 diabetes cases and 85 controls, before and after IA seroconversion. Results: Change in EAA significantly differed between cases and controls (p=0.02). EAA significantly decreased in cases, from pre-IA to post-IA seroconversion by 0.367 units (95% CI −0.64 to 0.09, p=0.01), but not in controls (0.045, 95% CI 0.23 to 0.32, p=0.75). Conclusion: These results suggest that EAA occurs in children who develop type 1 diabetes prior to IA seroconversion, highlighting the potential role of early environmental stressors in disease pathogenesis.

Context: Increased levels of 25-hydroxyvitamin D (25OHD) have been protective against islet autoimmunity (IA), a preclinical type 1 diabetes (T1D) disease state. However, the role of 25OHD and downstream metabolites in progression from IA to T1D is not well understood. Objective: We hypothesized that downstream vitamin D metabolites and metabolite ratios would be associated with progression from IA to T1D. Methods: Among participants at high genetic risk for T1D who developed IA (n = 143) in the Diabetes Autoimmunity Study in the Young (DAISY), a T1D birth cohort study, we quantified vitamin D3, 25OHD2, 3-epi-25OHD3, 25OHD3, 24,25(OH)2D3, and 1α,25(OH)2D3 metabolites from plasma samples using LC-MS/MS. We calculated the vitamin D metabolite ratio (VMR) (ie, 24,25(OH)2D3/25OHD3) and the epimer ratio (3-epi-25OHD3/25OHD3). We also tested the correlation between metabolite levels and gene expression in a subset of participants (n = 53). Results: A total of 57/143 progressed to T1D. Higher VMR (hazard ratio (HR) per 1 SD increase: 0.65; 95% CI: 0.49-0.88) and levels of 24,25(OH)2D3 (HR per 1 SD increase: 0.72; 95% CI: 0.55-0.94) at IA seroconversion were associated with a lower risk of progression to T1D, adjusting for seroconversion age, season, HLA-DR3/4 genotype, and ancestry. Functional enrichment analysis suggests higher VMR resulted in a gene expression pattern in whole blood characteristic of decreased activation of inflammatory pathways related to neutrophil infiltration. Conclusion: A higher VMR, a more functional measure of vitamin D status, was protective against T1D progression, perhaps by decreasing activation of inflammatory pathways.

OBJECTIVE: Multiple studies have reported an inverse association between self-reported smoking during pregnancy and offspring type 1 diabetes (T1D) risk. We investigated the association between DNA methylation (DNAm) smoke exposure scores, parental self-reported smoking, and islet autoimmunity (IA) and T1D risk in children at high risk of T1D. RESEARCH DESIGN AND METHODS: We used longitudinal data from the Diabetes Autoimmunity Study in the Young cohort, including 205 IA case and 206 control participants (87 and 88 were T1D case and control participants, respectively), matched by age, race/ethnicity, and sample availability. DNAm profiles were obtained from cord or peripheral blood using the Infinium Human Methylation 450K or EPIC BeadChip. Three published DNAm smoking scores were calculated at every time point. To estimate in utero smoke exposure, participant-specific intercepts were derived from mixed-effects models of longitudinal DNAm scores. These intercepts strongly correlated with cord blood scores (r = 0.85–0.95; n = 179), indicating their utility as proxies for in utero smoke exposure. Associations with IA/T1D were evaluated using logistic regression, adjusting for HLA-DR3/4, first-degree relative status, and sex. RESULTS: Multivariable models showed both maternally reported smoking during pregnancy and higher DNAm smoking scores to be associated with lower risk of IA and T1D. Maternal smoking showed a strong inverse association with IA (odds ratio [OR] 0.24; 95% CI 0.10–0.54). Rauschert and McCartney DNAm scores showed consistent inverse associations with both outcomes (OR 0.65–0.83 for SD increase). CONCLUSIONS: Our study supports existing literature indicating in utero smoke exposure is associated with reduced IA and T1D risk. Further research is essential to uncover the underlying mechanisms.

Seroconversion (SV) marks the initiation of islet autoimmunity (IA) and pre-clinical phase of type 1 diabetes (T1D), yet the contributions of immune cells beyond cytotoxic T cells remain unclear. We applied high-resolution immune cell-type deconvolution using peripheral blood DNA methylation data from nested case-control samples of the Diabetes Autoimmunity Study in the Young (DAISY; n=151) and The Environmental Determinants of Diabetes in the Young (TEDDY; n=166) to estimate immune cell proportions before SV (pre-SV) and after SV (SV) and construct functional ratios, such as the neutrophil-to-lymphocyte ratio (NLR). Using linear models, we evaluated differences between T1D cases and controls at pre-SV, SV, and the change across timepoints. Pre-SV, T1D cases had higher NLR and lower CD4T/CD8T cell ratios. At SV, the combined B-CD4T-CD8T memory/naïve ratio was reduced in cases. From pre-SV to SV, T1D cases also showed attenuated increases in NLR, B-memory/naïve, and B– CD4T–CD8T memory/naïve ratios. These patterns may reflect delayed or disrupted immune maturation, with persistence of naïve cells or impaired transition to memory subsets following antigen exposure. Our findings suggest that changes in innate and adaptive immune dynamics emerge early in the disease process, and that peripheral immune cell ratios may serve as informative biomarkers for risk stratification and mechanistic insight for development of T1D. Article Highlights Why did we undertake this study? We undertook this study to examine immune cell profiles around a critical time window of IA seroconversion for children at an increased risk of developing T1D. What is the specific question(s) we wanted to answer? We wanted to answer questions regarding immune cell ratio differences between T1D cases and controls in three specific instances: i) pre-SV, ii) SV, and iii) the change pre-SV to SV. What did we find? We found differences in immune cell ratios between T1D cases and controls before, during, and between IA periods, which have potential etiological and pathophysiological implications. What are the implications of our findings? Our findings highlight the complexity of immunodynamics around the time of IA seroconversion and the potential for immune cell ratios to aid in T1D risk stratification and intervention.

Context: This is the first study to examine the association between variants of the glucagon-like-peptide-1 receptor gene (GLP-1R) and metabolic characteristics among youth. Objective: We explored separate associations of 3 GLP-1R polymorphisms (rs10305420, rs6923761, and rs1042044) with body mass index (BMI) trajectories and markers of glucose-insulin homeostasis. Methods: Mixed models examined associations between GLP-1R polymorphisms and trajectories of BMI. Linear models examined associations of GLP-1R polymorphisms with glucose and insulin concentrations across oral glucose tolerance test (OGTT), insulin sensitivity (HOMA2-IR), insulin secretion (insulinogenic index and HOMA2-%B), and β-cell function (oral disposition index). Results: Rs10305420 and rs6923761, but not rs1042044, were associated with growth and metabolic characteristics in early life. Rs6923761 genotype GG was associated with faster BMI growth velocity, when compared to carriers of the minor allele (difference in velocity [95% CI]: 0.16/year [0.07-0.24] at age 10), which led to significantly higher average BMI by age 16 (average difference [95% CI]: 1.29 [0.22-2.37]). Rs10305420 CC and rs6923761 GG genotypes had higher HOMA2-IR (β [95% CI]: 1.19% [1.06-1.32] and 1.13% [1.01-1.26], respectively) compared to minor allele carriers. Rs10305420 CC had higher HOMA2-%B (β [95% CI]: 1.09% [1.01-1.17]), and higher stimulated insulin secretion at 30 minutes (β [95% CI]: 27.62 μIU/mL [3.00-25.24]) and 120 minutes (β [95% CI]: 18.94 μIU/mL [1.04-36.84]), when compared to carriers of the minor allele. Conclusion: GLP-1R polymorphisms are associated with faster BMI growth across development, and lower estimated insulin sensitivity and higher compensatory insulin secretion during adolescence. GLP-1R polymorphisms should be considered in future pediatric studies of genetic susceptibility for obesity and diabetes.

Background: An animal’s ability to discriminate between differing wavelengths of light (i.e., color vision) is mediated, in part, by a subset of photoreceptor cells that express opsins with distinct absorption spectra. In Drosophila R7 photoreceptors, expression of the rhodopsin molecules, Rh3 or Rh4, is determined by a stochastic process mediated by the transcription factor spineless . The goal of this study was to identify additional factors that regulate R7 cell fate and opsin choice using a Genome Wide Association Study (GWAS) paired with transcriptome analysis via RNA-Seq. Results: We examined Rh3 and Rh4 expression in a subset of fully-sequenced inbred strains from the Drosophila Genetic Reference Panel and performed a GWAS to identify 42 naturally-occurring polymorphisms—in proximity to 28 candidate genes—that significantly influence R7 opsin expression. Network analysis revealed multiple potential interactions between the associated candidate genes, spineless and its partners. GWAS candidates were further validated in a secondary RNAi screen which identified 12 lines that significantly reduce the proportion of Rh3 expressing R7 photoreceptors. Finally, using RNA-Seq, we demonstrated that all but four of the GWAS candidates are expressed in the pupal retina at a critical developmental time point and that five are among the 917 differentially expressed genes in sevenless mutants, which lack R7 cells. Conclusions: Collectively, these results suggest that the relatively simple, binary cell fate decision underlying R7 opsin expression is modulated by a larger, more complex network of regulatory factors. Of particular interest are a subset of candidate genes with previously characterized neuronal functions including neurogenesis, neurodegeneration, photoreceptor development, axon growth and guidance, synaptogenesis, and synaptic function.