Neuron-Glia-Ratio-Like Approach Evidenced for Limited Variability and In-Aggregate Circadian Shifts in Cortical Cell-Specific Transcriptomes

Regardless of shifts in levels of individual transcripts, it remains elusive whether natural variability in cell-specific transcriptomes within the cerebral cortex is limited in aggregate. It is also unclear whether cortical cell-specific transcriptomes might change dynamically in absence of cell number changes. Total variation in neuron- and glia-specific in-aggregate transcriptomes could be identified in a model-free way via glia-neuron ratio approach, by univariate median-to-median ratios comparing integral levels of cell-specific transcripts within a tissue sample. When deleterious, regenerative or developmental events affecting cortical cell numbers were subtle, median-to-median ratios demonstrated within-group variability not exceeding <20-25% in most cases. These levels of total variability might be explained in part by limited (~5-10%) circadian and stress-induced shifts in cell-specific cortical transcriptomes. Relevant in-aggregate transcriptomic alterations were identified after shifts in cell numbers induced by well-validated deleterious events including ischemia, traumatic injury, microglia's activation/depletion or specific mutations. Cortical median-to-median ratios also follow naturally occurring changes in the numbers of excitatory, inhibitory neurons and glial cells during perinatal brain development. These findings characterize cortical cell-specific transcriptomes as subjects to circadian shifts and lifetime events, urging the importance of reporting full details on an origin of any transcriptomic sample collected in vivo.

Reporting only relative effect measures was potentially misleading: some good practices for improving the soundness of epidemiological results

OBJECTIVE

In the medical and epidemiological literature there is a growing tendency to report an excessive number of decimal digits (often three, sometimes four), especially when measures of relative occurrence are small; this can be misleading.

STUDY DESIGN AND SETTING

We combined mathematical and statistical reasoning about the precision of relative risks with the meaning of the decimal part of the same measures from biological and public health perspectives.

RESULTS

We identified a general rule for minimizing the mathematical error due to rounding of relative risks, depending on the background absolute rate, which justifies the use of one or more decimal digits for estimates close to 1.

CONCLUSIONS

We suggest that both relative and absolute risk measures (expressed as a rates) should be reported, and two decimal digits should be used for relative risk close to 1 only if the background rate is at least 1/1,000 py. The use of more than two decimal digits is justified only when the background rate is high (ie, 1/10 py).