Probabilistic early warning signals

Ecological communities and other complex systems can undergo abrupt and long-lasting reorganization, a regime shift, when deterministic or stochastic factors bring them to the vicinity of a tipping point between alternative states. Such changes can be large and often arise unexpectedly. However, theoretical and experimental analyses have shown that changes in correlation structure, variance, and other standard indicators of biomass, abundance, or other descriptive variables are often observed prior to a state shift, providing early warnings of an anticipated transition. Natural systems manifest unknown mixtures of ecological and environmental processes, hampered by noise and limited observations. As data quality often cannot be improved, it is important to choose the best modeling tools available for the analysis.We investigate three autoregressive models and analyze their theoretical differences and practical performance. We formulate a novel probabilistic method for early warning signal detection and demonstrate performance improvements compared to nonprobabilistic alternatives based on simulation and publicly available experimental time series.The probabilistic formulation provides a novel approach to early warning signal detection and analysis, with enhanced robustness and treatment of uncertainties. In real experimental time series, the new probabilistic method produces results that are consistent with previously reported findings.Robustness to uncertainties is instrumental in the common scenario where mechanistic understanding of the complex system dynamics is not available. The probabilistic approach provides a new family of robust methods for early warning signal detection that can be naturally extended to incorporate variable modeling assumptions and prior knowledge.

Taxonomic signatures of cause-specific mortality risk in human gut microbiome

The collection of fecal material and developments in sequencing technologies have enabled standardised and non-invasive gut microbiome profiling. Microbiome composition from several large cohorts have been cross-sectionally linked to various lifestyle factors and diseases. In spite of these advances, prospective associations between microbiome composition and health have remained uncharacterised due to the lack of sufficiently large and representative population cohorts with comprehensive follow-up data. Here, we analyse the long-term association between gut microbiome variation and mortality in a well-phenotyped and representative population cohort from Finland (n = 7211). We report robust taxonomic and functional microbiome signatures related to the Enterobacteriaceae family that are associated with mortality risk during a 15-year follow-up. Our results extend previous cross-sectional studies, and help to establish the basis for examining long-term associations between human gut microbiome composition, incident outcomes, and general health status.

Maternal prenatal psychological distress and hair cortisol levels associate with infant fecal microbiota composition at 2.5 months of age

BACKGROUND

Maternal prenatal stress associates with infant developmental outcomes, but the mechanisms underlying this association are not fully understood. Alterations in the composition and function of infant intestinal microbiota may mediate some of the observed health effects, a viewpoint that is supported by animal studies along with a small human study showing that exposure to prenatal stress modifies the offspring's intestinal microbiota. In the current study, we aim to investigate the associations between maternal prenatal psychological distress (PPD) and hair cortisol concentration (HCC) with infant fecal microbiota composition in a large prospective human cohort.

METHODS

The study population was drawn from FinnBrain Birth Cohort Study. Maternal PPD was measured with standardized questionnaires (EPDS, SCL, PRAQ-R2, Daily Hassles) three times during pregnancy (n = 398). A measure addressing the chronicity of PPD was composed separately for each questionnaire. HCC was measured from a five cm segment at gestational week 24 (n = 115), thus covering the early and mid-pregnancy. Infant fecal samples were collected at the age of 2.5 months and analyzed with 16S rRNA amplicon sequencing.

RESULTS

Maternal chronic PPD (all symptom measures) showed positive associations (FDR < 0.01) with bacterial genera from phylum Proteobacteria, with potential pathogens, in infants. Further, chronic PPD (SCL, PRAQ-R2, and Daily Hassles negative scale) associated negatively with Akkermansia. HCC associated negatively with Lactobacillus. Neither maternal chronic PPD nor HCC associated with infant fecal microbiota diversity.

CONCLUSION

Chronic maternal PPD symptoms and elevated HCC associate with alterations in infant intestinal microbiota composition. In keeping with the earlier literature, maternal PPD symptoms were associated with increases in genera fromProteobacteria phylum. Further research is needed to understand how these microbiota changes are linked with later child health outcomes.

Migration waves to the Baltic Sea region

In this study, the population history of the Baltic Sea region, known to be affected by a variety of migrations and genetic barriers, was analyzed using both mitochondrial DNA and Y-chromosomal data. Over 1200 samples from Finland, Sweden, Karelia, Estonia, Setoland, Latvia and Lithuania were genotyped for 18 Y-chromosomal biallelic polymorphisms and 9 STRs, in addition to analyzing 17 coding region polymorphisms and the HVS1 region from the mtDNA. It was shown that the populations surrounding the Baltic Sea are genetically similar, which suggests that it has been an important route not only for cultural transmission but also for population migration. However, many of the migrations affecting the area from Central Europe, the Volga-Ural region and from Slavic populations have had a quantitatively different impact on the populations, and, furthermore, the effects of genetic drift have increased the differences between populations especially in the north. The possible explanations for the high frequencies of several haplogroups with an origin in the Iberian refugia (H1, U5b, I1a) are also discussed.

MtDNA polymorphism in the Hungarians: comparison to three other Finno-Ugric-speaking populations

Mitochondrial DNA sequence variation as well as restriction site polymorphisms were examined in 437 individuals from four Finno-Ugric-speaking populations. These included the Hungarians (Budapest region and the Csángós from Hungary and Romania), the Finns and two Saami groups from northeastern Finland (Inari Saami and Skolt Saami), and the Erzas from central Russia. The mtDNA data obtained in this study were combined with our previous data on Y chromosomal variation for eight different loci in these populations. The genetic variation observed among the Hungarians resembled closely that found in other European populations. The Hungarians could not be distinguished from the neighboring populations (e.g., the Austrians) any more than from their Finno-Ugric linguistic relatives.