Hi , I'm trying to get DEG from the old and young group with DESeq2, but there are no significant genes. the adjusted p values are very close to 1. Could someone help me find out the problem?

here are my count data and coldata

 Gene Small_Intestine_34_m_3  Small_Intestine_22_m_18 Small_Intestine_56_m_21

1 0610005C13Rik                    477                     639                     760

2      Trappc2b                    215                     179                     187

3 0610009L18Rik                     12                      18                      12

4         Sanbr                     93                      59                     101

5 0610010K14Rik                     14                      17                      34

6      Ncbp2as2                    537                     552                     470


 tissue age sex age_sex               sample_id agegroup

Small_Intestine_34_m_3  Small_Intestine   3   m     3_m  Small_Intestine_34_m_3    young

Small_Intestine_22_m_18 Small_Intestine  18   m    18_m Small_Intestine_22_m_18      old

Small_Intestine_56_m_21 Small_Intestine  21   m    21_m Small_Intestine_56_m_21      old

Small_Intestine_41_m_1  Small_Intestine   1   m     1_m  Small_Intestine_41_m_1    young

Small_Intestine_8_m_15  Small_Intestine  15   m    15_m  Small_Intestine_8_m_15      old

Small_Intestine_24_f_3  Small_Intestine   3   f     3_f  Small_Intestine_24_f_3    young

dds <- DESeqDataSetFromMatrix(countData=expr_filt2, 
                              colData=subset_md, 
                              design=~agegroup, tidy = TRUE)
#run DESeq2
dds$agegroup <- relevel(dds$agegroup, ref="old")
dds <- DESeq(dds)

#store/view results
res <- results(dds)

there are no significant genes. the adjusted p values are very close to 1. Could someone help me find out the problem?

The data are telling you something.