Publications

We have developed a new point-of-care test to diagnose iron deficiency anemia by eye or using machine learning.

Introduction: Plasma metabolomic profiles of BMI are associated with type 2 diabetes (T2D) risk but none have examined saliva or combined information from multiple biofluids. Our aim was to identify plasma, saliva, and plasma-saliva multi-fluid metabolomic profiles of BMI and waist circumference (WC) and examine their associations with diabetes progression. Methods: We included 911 participants from the San Juan Overweight Adult Longitudinal Study, a 3-year prospective cohort of overweight Puerto Ricans. At baseline, using LC-MS, we quantified metabolites from saliva (n=635) and plasma (n=1,051). We used elastic net regression with 10-fold cross-validation to identify metabolomic profiles from plasma, saliva, and plasma and saliva (multi-fluid) that were predictive of BMI and WC. We used Cox-proportional hazard models to evaluate associations between metabolomic profiles and diabetes progression adjusting for age, sex, socioeconomic factors, lifestyle, and medication use. Results: For BMI metabolomic profiles, we identified 207 metabolites in plasma, 118 metabolites in saliva, and 225 in the multi-fluid profile. For WC, we identified 157, 89, and 210 metabolites for plasma, saliva, and multi-fluid profiles, respectively. Highly positively weighted metabolites across all BMI and WC metabolomic profiles included those in pathways of alanine and aspartate metabolism, purine metabolism, and sphingomyelins. BMI and WC metabolomic profiles were highly correlated (r=0.80-0.88). Each SD increase in saliva, but not plasma or multi-fluid, metabolic profile of BMI was significantly associated with diabetes progression (Table). Saliva, but not plasma or multi-fluid, metabolomic profile of WC was significantly associated with progression from pre-diabetes to T2D. All associations became stronger after further adjustment for anthropometric measures of BMI and WC. Conclusion: Saliva is an underexplored and easily accessible biofluid to measure metabolites that associate with diabetes progression.

Abstract Background Quantitative molecular data from urine are rare in epidemiology and genetics. NMR spectroscopy could provide these data in high throughput, and it has already been applied in epidemiological settings to analyse urine samples. However, quantitative protocols for large-scale applications are not available. Methods We describe in detail how to prepare urine samples and perform NMR experiments to obtain quantitative metabolic information. Semi-automated quantitative line shape fitting analyses were set up for 43 metabolites and applied to data from various analytical test samples and from 1004 individuals from a population-based epidemiological cohort. Novel analyses on how urine metabolites associate with quantitative serum NMR metabolomics data (61 metabolic measures; n = 995) were performed. In addition, confirmatory genome-wide analyses of urine metabolites were conducted (n = 578). The fully automated quantitative regression-based spectral analysis is demonstrated for creatinine and glucose (n = 4548). Results Intra-assay metabolite variations were mostly <5%, indicating high robustness and accuracy of urine NMR spectroscopy methodology per se. Intra-individual metabolite variations were large, ranging from 6% to 194%. However, population-based inter-individual metabolite variations were even larger (from 14% to 1655%), providing a sound base for epidemiological applications. Metabolic associations between urine and serum were found to be clearly weaker than those within serum and within urine, indicating that urinary metabolomics data provide independent metabolic information. Two previous genome-wide hits for formate and 2-hydroxyisobutyrate were replicated at genome-wide significance. Conclusion Quantitative urine metabolomics data suggest broad novelty for systems epidemiology. A roadmap for an open access methodology is provided.

Along with the increasing overweight and obesity trends among adults and children globally, numerous studies have suggested a strong association between maternal overweight and obesity among their offspring. We sought to report the prevalence and associated factors of intergenerational overweight and obesity among mother–child pairs in Malaysia from 2006 to 2015. Data were analysed from three waves of the Malaysian National Health and Morbidity Survey, a population-based cross-sectional study conducted in 2006, 2011 and 2015. A mother and the youngest child from each household formed ‘mother–child pairs’ and were grouped according to their body mass index categories. A multivariable logistic regression model was performed to determine the factors associated with overweight mother/overweight child pairs (OWM/OWC), with normal weight mother/normal weight child pairs (NWM/NWC) as the reference group. The prevalence of OWM/OWC increased from 15.3% to 21.7%, while the prevalence of NWM/NWC decreased from 28.4% to 23.8% between 2006 and 2015. Older maternal age and having primary and secondary education levels were positively associated with OWM/OWC. Conversely, older child age, Chinese ethnicity, large household size and low-income households were inversely associated with OWM/OWC. In conclusion, intergenerational weight gain is a worrisome trend in Malaysia. These findings may help in guiding priority setting for obesity prevention strategies in Malaysia.

'Piezoelectric Effect at Nanoscale' published in 'Encyclopedia of Nanotechnology'

The purpose of this study was to determine the co-occurrence of DSM- III-R personality disorders (PDs) with mood, anxiety, and substance use disorders in a young adult population. The members of the Northern Finland 1966 Birth Cohort Project, living in the city of Oulu with an age of 31 years (N = 1,609) were invited to participate in a two-phase field study. The SCID I and II were used as diagnostic instruments. One hundred and seventy-seven out of 321 interviewed subjects met the criteria for mood, anxiety, or substance use disorders. Altogether 72 (41%) of the subjects with an Axis I disorder met the criteria for at least one PD. The weighted co-occurrence rate of any PD varied from 28% for mood disorders to 47% for anxiety disorders. PDs, especially those in Cluster C, are highly associated with Axis I psychiatric disorders in population.

Moderately higher adiposity at age 18 years is associated with increased premature death in younger and middle-aged U.S. women.

To identify type 2 diabetes (T2D) susceptibility loci, we conducted genome-wide association (GWA) scans in nested case-control samples from two prospective cohort studies, including 2591 patients and 3052 controls of European ancestry. Validation was performed in 11 independent GWA studies of 10,870 cases and 73,735 controls. We identified significantly associated variants near RBMS1 and ITGB6 genes at 2q24, best-represented by SNP rs7593730 (combined OR=0.90, 95% CI=0.86-0.93; P=3.7x10(-8)). The frequency of the risk-lowering allele T is 0.23. Variants in this region were nominally related to lower fasting glucose and HOMA-IR in the MAGIC consortium (P<0.05). These data suggest that the 2q24 locus may influence the T2D risk by affecting glucose metabolism and insulin resistance.

Although schizotypal traits, such as anhedonia and aberrant perceptions, may increase the risk for schizophrenia-spectrum disorders, little is known about early-life characteristics that predict more pronounced schizotypal traits.To examine whether birth size or several other early-life factors that have been previously linked with schizophrenia predict schizotypal traits in adulthood.Participants of the Northern Finland 1966 Birth Cohort Study (n = 4976) completed a questionnaire on positive and negative schizotypal traits at the age of 31 years.Lower placental weight, lower birth weight and smaller head circumference at 12 months predicted elevated positive schizotypal traits in women after adjusting for several confounders (P<0.02). Moreover, higher gestational age, lower childhood family socioeconomic status, undesirability of pregnancy, winter/autumn birth, higher birth order and maternal smoking during pregnancy predicted some augmented schizotypal traits in women, some in men and some in both genders.The results point to similarities in the aetiology of schitzotypal traits and schizophrenia-spectrum disorders.

BACKGROUND: In recent decades, there has been an increase in the prevalence of childhood overweight in most high-income countries. Within northern Europe, prevalence tends to be higher in the UK compared with the Scandinavian countries. We aimed to study differences in body mass index (BMI) trajectories between large cohorts of children from UK and Scandinavian populations. METHODS: We compared BMI trajectories in participants from the English Avon Longitudinal Study of Parents and Children born in 1991-1993 (ALSPAC) (N = 6517), the Northern Finland Birth Cohorts born in 1966 (NFBC1966) (N = 3321) and 1986 (NFBC1986) (N = 4764), and the Danish Aarhus Birth Cohort born in 1990-1992 (ABC) (N = 1920). We used multilevel models to estimate BMI trajectories from 2 to 18 years. We explored whether cohort differences were explained by maternal BMI, height, education or smoking during pregnancy and whether differences were attributable to changes in the degree of skew in the BMI distribution. RESULTS: Differences in mean BMI between the cohorts were small but emerged early and persisted in most cases across childhood. Girls in ALSPAC had a higher BMI than all other cohorts throughout childhood, e.g. compared with the NFBC1986 BMI was 2.2-3.5% higher. For boys, the difference emerging over time (comparing the two NFBC's) exceeded the differences across populations (comparing NFBC1986, ABC and ALSPAC). BMI distribution demonstrated increasing right skew with age. CONCLUSION: Population-level differences between cohorts were small, tended to emerge very early, persisted across childhood, and demonstrated an increase in the right-hand tail of the BMI distribution.