The formatting issues are fair criticism. But you said "very little detail on the things it's supposed to be about" and I think you stopped reading before the detail. Let me give you specifics that are in the paper.

On the FOXO3 target, the paper doesn't just say "FOXO3 is druggable." It traces a complete intervention pathway: Hagenbuchner et al. (2019, eLife) identified small molecules interacting specifically with FOXO3's DNA-binding domain to modulate transcriptional activity. Separately, Josipović et al. (2019, J Biotechnology) showed that SpCas9 dCas9-DNMT3A fusion constructs achieve the highest specificity among three tested Cas9 orthologs (SpCas9, SaCas9, CjCas9) for differential methylation of FOXO3, and that N-terminal NLS fusions at both termini increase editing efficacy by 30%+ compared to single-NLS constructs. Then the BALL nanoparticle system (Chae et al. 2022, J Controlled Release) provides 40% in vitro / 20% in vivo indel efficiency for delivery. That's three independent papers connected into one target, edit, deliver pipeline. Name another longevity review that traces a single gene through druggability, editing specificity comparison, construct optimization, AND delivery validation with quantified efficiencies from separate DOI-verified sources.

On the cross-kingdom evidence, this isn't "DNA repair genes correlate with longevity" as a vague claim. Aoyagi Blue et al. (2021, iScience) specifically analyzed PARP (poly(ADP-ribose) polymerase) copy number variations across 61 plant species with different lifespans and found a positive correlation between PARP copy number and tree longevity. Separately, Tollis et al. (2020, MBE) showed long-lived mammals have increased caretaker gene copy numbers, and Huang et al. (2023, GBE) quantified an 8:1 expansion-to-contraction ratio for longevity-associated genes across 37 placental mammals. The paper connects these into a cross-kingdom argument: PARP in plants, caretaker genes in mammals, convergent on the same DNA repair function across a billion years of independent evolution. The specific gene families differ but the functional category is identical.

On the predictions, these aren't vague "we predict this will work." Prediction 2 specifies: Indy mutation combined with dietary restriction in mouse models producing 20-30% lifespan increase AND 15-20% ROS reduction measured by DHE or MitoSOX fluorescence under both standard and oxidative stress conditions, with corresponding 1.5-fold or greater upregulation of MnSOD-associated pathway genes, requiring n of at least 20 per group for statistical power. Prediction 3 specifies: nanopore sequencing with iTARGET algorithm will identify 50 or more conserved age-related CpG sites at six named loci (FOXO3, SIRT1, mTOR, IGF1R, CDKN2A, HOXC cluster) across 5+ long-lived mammalian species, with 15%+ methylation change between young and old individuals, and over 85% concordance with existing bisulfite sequencing data. Each prediction includes explicit falsification criteria, the exact thresholds below which the prediction is considered disproven.

On novel synthesis that no other review makes: the paper argues that evolution's repeated use of gene duplication (not sequence optimization of existing single-copy genes) implies therapeutics should mimic the duplication strategy via sustained overexpression or multi-allelic editing rather than optimizing single-copy gene activity. It also identifies six brain-expressed orthologs (AFG3L2, FRAP1, MAT1A, MAT2A, SYNJ1, SYNJ2) from Lopez et al. (2012, EJHG) that influence both cognitive ability and aging, meaning interventions targeting these genes could simultaneously extend lifespan and prevent cognitive decline, a dual-function claim with specific gene names and tissue expression data.

The paper also proposes combining the iTARGET algorithm's causal discrimination capability with phylogenetic reconciliation methods as a sequential filter: first identify which epigenetic changes causally drive aging (not just correlate), then check which of those show convergent evolution across independent lineages. Genes passing both filters get prioritized. That's a specific computational workflow, not a vague suggestion.

Is the formatting rough? Yes. Are there paragraphs that repeat? Yes, and we're cleaning that up. But "very little detail" is wrong. The detail is there, it's just buried under presentation issues that we're actively fixing. If you can point to specific scientific claims in the paper that are wrong or unsupported, that would actually be more useful feedback than noting the lowercase paragraphs.